An Integrated Inventory Model with Geometric Shipment Policy and Trade-Credit Financing under Stochastic Lead Time
|
|
- Lee Fowler
- 5 years ago
- Views:
Transcription
1 Volume 117 No , ISSN: (printed version); ISSN: (on-line version) url: ijpam.eu An Integrated Inventory Model with Geometric Shipment Policy and Trade-Credit Financing under Stochastic Lead Time S. Hemapriya 1 and R. Uthayakumar 1, The Gandhigram Rural Institute - Deemed University, Gandhigram. 1 hemapriya9194@gmail.com uthayagri@gmail.com Abstract This article explores a single-vendor and a single-buyer integrated production inventory system with main concern is on the trade-credit policy and lead time reduction. A geometric shipment policy is adopted to deliver the items to the buyer. In particular, the supplier offers a credit period that is less than the average duration of the inventory model. The objective of this study is to minimize the Joint Economic Total Cost (JETC) by simultaneously optimizing the order quantity, lead time and safety factor. An iterative algorithm of finding the optimal solution is developed and numerical examples are given to illustrate the results. AMS Subject Classification: 90B05. Key Words and Phrases: Integrated inventory model, Geometric shipment policy, Lead time reduction. 1 Introduction To succeed in the competitive business environment and to optimize performance, integrated policy is a new paradigm adopted by business organizations. Many organizations have begun to embrace the integrated policy as it enables shorter lead time and lower inventory cost. Thus, the integrated policy has drawn the attention of several researchers to study the effect of integration between a vendor and a buyer. [1 studied a model in which the shipment size increases geometrically. Hill developed the [1 model where the geometric growth rate in shipments size is a decision variable. Later, several researchers [3, [4 and [5 have developed integrated 01
2 production-distribution inventory models by extending the idea of [ and incorporating various realistic assumptions. But it is not always suitable in a realistic environment. In real life business via share marketing, trade credit financing becomes a influential tool to improve sales and reduce on-hand stock. This permissible delay in payments reduces the cost of holding stock since it reduces the amount of capital invested in stock for the duration of the permissible period. During the delay period the buyer can accumulate revenue on sales and earn interest on that revenue via share market investment or banking business. It makes economic sense for the distributor to delay period allowed by the producer. Wu established the continuous review inventory model with permissible delay in payments. [10 developed supply chain model with stochastic lead time, trade-credit financing and transportation discounts. [6 revealed that lead time could be reduced by investing an additional amount on hi-tech equipment, information technology, order expedite and logistics. The first attempt to formulate a probabilistic inventory model with lead time as decision variable was made by [7. By treating the lead time as a decision variable, [9 generalized [1 model and found that the joint total expected cost and lead time are less compared to that of [1 model. Researchers [8 have worked on lead time reduction by formulating integrated production-inventory models in a single-vendor and a single-buyer supply chain environment. In the aforesaid literature it is not clear that most of the integrated inventory models were developed under the assumption that the products are delivered in equal sized shipments. Therefore, the efforts has been taken by the authors to adopt a geometric shipment policy so as to fill this remarkable gap in the inventory literature. Here an integrated inventory model with geometric shipment policy and trade-credit financing under stochastic lead time is discussed. Notations and assumptions.1 Notations We need the following assumptions and notations, to develop the mathematical model of this model. The following terminology is used: Q Vendor s production batch size q 1 Size of the first shipment from the vendor to the buyer q i Size of the i th shipment D Average demand per year P Production rate of the buyer P > D A The ordering cost of the buyer per order S Vendor s setup cost per setup λ Geometric growth factor h b The holding cost rate of the buyer per unit per unit time h v The holding cost rate of the vendor per unit per unit time n Number of lots in which the item are delivered from the vendor to the buyer L Length of lead time β Fraction of the shortage that will be backordered at the buyer s end, 0 β < 1 π 0 Marginal profit per unit 0
3 π x Price discount offered on backorder by the vendor per unit, 0 π x π 0 R Reorder point of the buyer k Safety factor a Fixed component of the transportation cost, ($/shipment) b Variable component of the transportation cost, ($/unit item/shipment) R(L) Lead time crashing cost i b Buyer s interest or opportunity cost in annual percentage i s Vendor s interest or opportunity cost in annual percentage N Length of credit-period per unit time pc Purchasing cost per unit time. Assumptions The fundamental assumptions used in developing the model are as follows: 1. The system deals with a single-vendor and a single-buyer.. The reorder point R equals the sum of the expected demand during lead time and safety stock (SS) and SS=k standard deviation of lead time demand. (i.e)., R = µl + kσ L where k is the safety factor. 3. Replenishments are made when the on hand inventory reaches the reorder point R. 4. The buyer orders a lot size of Q units and the vendor produces them with a finite production rate P in units per unit time in one setup. Produced items are supplied to the buyer in n unequal sized shipments. 5. The trade-credit financing is used to make it a cost-reduced supply chain. 6. The transportation cost is a + bq where a is the fixed cost per shipment, and b is the unit transportation cost per item. 3 Model Development Production and delivery are arranged as follows: The vendor produces Q units at one set-up with a finite production rate P (P > D). Consider the production batch of size Q which is made up of n unequal-sized shipments which are delivered to the buyer and the size of the i t h shipment within a batch is q i = βq i 1 = β i 1 q 1, i =, 3,..., n and represents the lot size of the first shipment. Therefore, the total batch production lot size is, Q = n q i = i=1 n i=1 λ i 1 q 1 = q 1(λ n 1) (λ 1) and the cycle length of the inventory is T = Q D = q 1(λ n 1) D(λ 1) 03
4 3.1 Buyer s Perspective The buyer receives a lot of q i units in each shipment which could be utilized during the time period q i. So the average inventory of the buyer during the time period q i D D is q i which gives the time-weighted inventory during a complete production cycle as, n i=1 q i D = n i=1 Therefore, the average inventory of the buyer is, (λ i 1 q 1 ) D = q 1(λ n 1) D(λ 1) q1(λ n 1) D(λ 1) /q 1(λ n 1) D(λ 1) = q 1(λ n + 1) (λ + 1) The buyer s expected annual total cost per unit time is the sum of the ordering cost, holding cost, transportation cost, stock-out cost and the lead time crashing cost and is given by, ET C b (q 1, k, L, n) = [ A + (π x β + π 0 (1 β))σ nd(λ 1) Lψ(k) + F + R(L) q 1 (λ n 1) [ q1 (λ n + 1) h b (λ + 1) + kσ L + (1 β)σ Lψ(k) (1) 3. Vendor s Perspective The buyer order a lot size of Q units and the vendor produces them at the rate of P > D and supplies them in n unequal-sized shipments. When the production process is about to start, the vendor s inventory level is zero and there are Dq 1 units P in the buyer s inventory which is just first shipment arrives. Then the vendor s total inventory level increases at a rate of P D units and it reaches the maximum height of, Dq 1 + (P D) q 1(λ n 1). P P (λ 1) The vendor s expected annual total cost per unit time is the sum of setup cost and the holding cost is given by, ET C v (q 1, n) = [ SD(λ 1) q 1 (λ n 1) + h Dq1 v P + q 1(P D)(λ n 1) q 1(λ n + 1) () P (λ 1) (λ + 1) 4 Integrated Approach The objective of this section is to determine the optimal values of the decision variables by minimizing the expected total cost per unit time and the buyer s expected annual total cost per unit time. Therefore, the joint expected total cost per unit 04
5 time of the integrated system is, JET C(q 1, k, L, n) = ET C b (q 1, k, L, n) + ET C v (q 1, n) [( = A + S ) + (π x β + (1 β)π 0 )σ Lψ(k) + F + R(L) n [ nd(λ 1) q 1 (λ n 1) + h q1 (λ n + 1) b (λ + 1) + kσ L + (1 β)e(x R) + [ Dq1 +h v P + q 1(P D)(λ n 1) q 1(λ n + 1) P (λ 1) (λ + 1) (3) To make the profitable supply chain an attempt of trade-credit policy is used. During the credit period, the buyer saves his/her total interest by using the trade-credit policy which is similar to [10. Thus the trade-credit cost is for the buyer which is offered by the vendor is defined as, pc(q DN) i s D D pcn i b D pcni b(1 β) Dβ Therefore, the trade-credit cost for the buyer per unit time is, pc( q 1(λ n 1) DN) λ 1 D pcn i b (λ 1) pcni b(1 β)(λ 1) q 1 (λ n 1) q 1 (λ n 1) βq 1 (λ n 1) Therefore, the above problem reduces to, JET C(q 1, k, L, n) = ET C b (q 1, k, L, n) + ET C v (q 1, n) [( = A + S ) + (π x β + (1 β)π 0 )σ Lψ(k) + F + R(L) n [ nd(λ 1) q 1 (λ n 1) + h q1 (λ n + 1) b (λ + 1) + kσ L + (1 β)e(x R) + [ Dq1 +h v P + q 1(P D)(λ n 1) q 1(λ n + 1) P (λ 1) (λ + 1) D pcn i b (λ 1) q 1 (λ n 1) pcni b(1 β)(λ 1) βq 1 (λ n 1) + pc( q 1(λ n 1) λ 1 DN) q 1 (λ n 1) At first for fixed (q 1, k, n), JET C(q 1, k, L, n) is a strictly concave in L due to the fact that, [ L JET C(q 1, k, S, θ, n) = (π x β + π 0 (1 β )) σψ(k) nd(β 1) L c i (β n 1) + h b L [kσ + (1 β )σψ(k) L JET C(q 1, k, S, θ, n) = 1 [(π L 3 x β + π 0 (1 β ))σψ(k) h b [kσ + (1 β )σψ(k) < 0 nd(β 1) (β n 1) (4) 05
6 Thus, JET C(q 1, k, L, n) is concave in L [L i, L i 1. Therefore, for fixed (q 1, k, n), the minimum value of JET C(q 1, k, L, n) on L lies at the end point of the interval [L i, L i 1. Secondly, if we relax the integer constraint on n, it is possible to note that JET C(q 1, k, L, n) is strictly convex in n, for fixed (q 1, k, L), L [L i.l i 1 and noticing that, n JET C(q 1, k, L, n) = ( ) [ [ Y D(λ 1) (λ n 1) n log λe n log λ SD(λ 1) log λe n log λ q 1 (λ 1) q 1 (λ n 1) [ q 1 log λ +(h B h v ) log λen + h vq 1 (P D) log λe n log λ (λ + 1) P (λ 1) + pci sq 1 log λe n log λ (λ 1) + pcd N i s (λ 1) q 1 (n log λ n log λ + (λ n 1)) n JET C(q 1, k, L, n) = where Y = M log λλn (λ n 1) 3 {λn nλ n SD(λ 1)(log λ) log λ} + (λ n + 1) q 1 (λ n 1) 3 + (h b h v )q 1 (log λ) λ n + h vq 1 (P D)(log λ) λ n (λ + 1) P (λ 1) pci s q 1 (log λ) λ n pcd N i s (λ 1) + (λ 1) q 1 ( log λλ n + n(log λ) λ n ) > 0 and M = [ (A + S n) + (πx β + (1 β)π 0 )σ Lψ(k) + F + R(L) ( ) Y D(λ 1) q 1 The above equation proposes that the Joint expected total cost is strictly convex in n for fixed (q 1, k, L),[L i, L i 1 and with the aid of taking account of equation 4. So we want to able to take the derivatives of JET C(q 1, k, L, n) with respect to q 1, and to attain, q 1 JET C(q 1, k, L, n) = 1 q 1 q 1 = [ ( A + S ) n + (π x β + (1 β)π 0 )σ Lψ(k) + a + R(L) nd(λ 1) + pcdn n (i s i b ) pcni b(1 β) βnd +h v [ D P + (P D)(λn 1) P (λ 1) (λn + 1) (λ + 1) Solving the above equation 5, we bear the value of q 1 as, [ [ ( ) A + S n + (πx β + (1 β)π 0 )σ Lψ(k) + a + R(L) + pcdn n (h b h v ) ( (λ n +1) (λ+1) ) [ D + h v + (P D)(λn 1) P P (λ 1) (λ n 1) + h b [ (λ n + 1) (λ + 1) + pci s(λ n 1) (λ 1) (i s i b ) pcni b(1 β) βnd + pcis(λn 1) (λ 1) Similarly for fixed (q 1, k, L),L [L i, L i 1 and with the aid of taking account of equation 4, so we want to able to take the derivatives of JET C(q 1, k, L, n) with respect to k and to attain, k JET C(q 1, k, L, n) = σ L [ ( ) nd(λ 1) (π x β + π 0 (1 β)) q 1 (λ n 1) + (1 β)h b (Φ(k) 1) + h b (7) (5) nd(λ 1) (λ n 1) 1 (6 06
7 Solving the above equation 7, we get the value of k and to attain, Φ(k) = 1 h b q 1 (λ n 1) (π x β + π 0 (1 β))nd(λ 1) + (1 β)h b q 1 (λ n 1) Moreover, it can be shown that the SOSC are satisfied since the Hessian matrix is positive definite at point (q 1, k) (see the appendix for the proof). Algorithm Step 1: Set n = 1. Step : Find Q and k for fixed n. Step 3: For every L i, i = 1,,..., n perform steps (3.1) to (3.3). 3.1 Set k (1) i = 0[implies ψ(k i ) (1) = , Φ(k i ) (1) = Substitute k (1) i = 0 and in equation 6 and evaluate q (1) i Utilizing q (1) i1 to determine the values of k () i from equation Repeat (3.1) to (3.3) until no change occurs in the values of q 1i and k i. Denote the solutions by (q i1, k i ). Step 4: Use equation 4 find the corresponding joint expected total cost JET C(q i1, k i, L, n) for i = 1,,..., n. Step 5: Find MinJET C(qi1, ki, L, n) for i = 1,,..., n and denote it by JET C(q(n)1, k (n), L, n)=min JET C(qi1, ki, L, n) and (q(n)1, k (n), L, n) are the optimal solutions for the given n. Step 6: Replace n by n+1 and repeat steps () to (5) to get JET C(q(n)1, k (n), L, n). Step 7: If JET C(q(n)1, k (n), L, n) JET C(q (n 1)1, k (n 1), L, n) then go to step 6 otherwise go to step 8. Step 8: Set (q 1, k, L, n) = (q (n 1)1, k (n 1), L, n) and JET C(q 1, k, L, n) is the optimal solution. 5 Numerical Results In this section, to illustrate the above solution procedure we consider the adaptive parameters similar to that proposed by Lin. The optimal values of the decision variables are obtained by using the solution procedure and the MATLAB software. D =00 units/year, P =1000 units/year, A =$00/order, S =$1500/setup, a =$5/unit, b =$10/unit, h b =$5/unit, h v =$0/unit, =7, pi x =$100/unit, pi 0 =$300/unit, s =$75/unit, α =0.5, N =3, pc =$/unit, i b =0.06, i s =0.0. We solve the cases for which the geometric growth factor λ = 1.5,, and.5. For the given 3 values of λ, we use the proposed algorithm to find the optimal solution of the model and the optimal solutions are summarized in??.?? shows that when L =4 weeks and λ =.5 the ordered units could be supplied in third shipment with an initial lot size of 35 units and the joint expected total cost reduced to $4363$. (8) 07
8 Table 1: Comparison of the previous model vs. proposed model λ L n q 1 k F JET C Conclusion In this paper, we presented an integrated inventory model with geometric shipment policy and trade-credit financing under stochastic lead time. We then developed an exact algorithm that authorizes the optimization of ordering quantity, safety factor, transportation cost and lead time. Numerical example conferred that this optimization approach achieves a high level of efficiency, which may offer promising in practice. The model can be extended to embody price discount, various reduction factors etc. Acknowledgment The first author research work is supported by DST INSPIRE Fellowship, Ministry of Science and Technology, Government of India under the grant no. DST/INSPIRE/03/016/00457 and UGC-SAP, Department of Mathematics, The Gandhigram Rural Institute Deemed University, Gandhigram 6430, Tamilnadu, India. Appendix For a given value of L [L i, L i 1, we first obtain the Hessian matrix H as follows: H = [ JET C(q 1,k,L,n) q1 JET C(q 1,k,L,n) kq 1 For the first minor, one can easily obtain as, JET C(q 1,k,L,n) q 1 k JET C(q 1,k,L,n) q1 [ H 11 = det JET C(q q1 1, k, L, n) = q 3 1 [ ( A + S ) + (π x β + (1 β)π 0 )σ Lψ(k) n +a + R(L) + pcdn n (i s i b ) pcni b(1 β) βnd nd(β 1) (β n 1) Therefore, H 11 > 0 For the second minor, one can easily obtain easily as, H = det [ JET C(q 1,k,S,θ,L,n) q1 JET C(q 1,k,S,θ,L,n) kq 1 JET C(q 1,k,S,θ,L,n) q 1 k JET C(q 1,k,S,θ,L,n) k 08
9 ( [ ( = A + S ) + (π q1 3 x β + (1 β)π 0 )σ Lψ(k) + R(L) + a + pcdn n )( nd(β 1) σ [ ( L (β n 1) n (i s i b ) pcni b(1 β) βnd ) ) nd(β 1) (π x β + π 0 (1 β)) q 1 (β n 1) + (1 β)h b φ(k) ( [ nd(β 1) + (π q (β n x β + (1 β )π 0 )σ L(Φ(k) 1)) > 0 1) Since φ(k) > 0, ψ(k) > 0 and φ(k)ψ(k) [Φ(k) 1 > 0 for all k > 0. Therefore, H > 0. From the above derivations, all the principal minors of the Hessian matrix is positive. Hence the given Hessian Matrix H is positive definite at (q 1, k). References [1 S.K. Goyal, A one-vendor multi-buyer integrated inventory model: A comment. European Journal of Operations Research, 8, (1995), [ S.K. Goyal, A joint economic-lot-size model for purchaser and vendor: A comment. Decision Sciences, 19, (1988), [3 M.A. Hoque, S.K. Goyal, A heuristic solution procedure for an integrated inventory system under controllable lead-time with equal or unequal sized batch shipments between a vendor and a buyer, International Journal of Production Economics, 10, (006), [4 A. Pandey, M. Masin, V. Prabhu, Adaptive logistic controller for integrated design of distributed supply chains, Journal of Manufacturing Systems, 6, (007), [5 J.T. Teng, L.E. Cardenas-Barron, K.R. Lou, The economic lot size of the integrated vendor-buyer inventory system derived without derivatives: a simple derivation, Applied Mathematics and Computation, 1, (011), [6 S.L. Hsu, C.C. Lee, Replenishment and lead time decisions in manufacturerretailer chains, Transportation Research Part E: Logistics and Transportation Review, 45, (009), [7 C.J. Liao, C.H. Shyu, An analytical determination of lead time with normal demand, International Journal of Operations and Production Management, 11, (1991), [8 L.Y. Ouyang, K.S. Wu and C.H. Ho, An integrated vendorbuyer inventory model with quality improvement and lead time reduction, International Journal of Production Economics 108, (007), [9 J.C.H. Pan, J.S. Yang, A study of an integrated inventory with controllable lead time, 40, (00),
10 [10 S.J. Kim, B. Sarkar, Supply Chain Model with Stochastic Lead Time, Trade- Credit Financing, and Transportation Discounts, Mathematical Problems in Engineering, (017). 10
11 11
12 1
Mixture inventory model in fuzzy demand with controllable lead time
Mixture inventory model in fuzzy demand with controllable lead time Jason Chao-Hsien Pan Department of Industrial Management National Taiwan University of Science and Technology Taipei 106 Taiwan R.O.C.
More information2. Assumptions and Notation
Volume 8 o. 08, 77-735 ISS: 34-3395 (on-line version) url: http://acadpubl.eu/hub ijpam.eu A IVETORY MODEL FOR DETERIORATIG ITEMS WITHI FIITE PLAIG HORIZO UDER THE EFFECT OF PERMISSIBLE DELAY AD PRESERVATIO
More informationBuyer - Vendor incentive inventory model with fixed lifetime product with fixed and linear back orders
National Journal on Advances in Computing & Management Vol. 5 No. 1 April 014 1 Buyer - Vendor incentive inventory model with fixed lifetime product with fixed and linear back orders M.Ravithammal 1 R.
More information7.1 INTRODUCTION. In this era of extreme competition, each subsystem in different
7.1 INTRODUCTION In this era of extreme competition, each subsystem in different echelons of integrated model thrives to improve their operations, reduce costs and increase profitability. Currently, the
More informationAn Integrated Just-In-Time Inventory System with Stock-Dependent Demand
BULLETIN of the MALAYSIAN MATHEMATICAL SCIENCES SOCIETY http:/math.usm.my/bulletin Bull. Malays. Math. Sci. Soc. (2) 37(4) (2014), 1085 1097 An Integrated Just-In-Time Inventory System with Stock-Dependent
More informationResearch Article A Partial Backlogging Inventory Model for Deteriorating Items with Fluctuating Selling Price and Purchasing Cost
Advances in Operations Research Volume 2012, Article ID 385371, 15 pages doi:10.1155/2012/385371 Research Article A Partial Backlogging Inventory Model for Deteriorating Items with Fluctuating Selling
More informationFuzzy Inventory Model for Imperfect Quality Items with Shortages
Annals of Pure and Applied Mathematics Vol. 4, No., 03, 7-37 ISSN: 79-087X (P), 79-0888(online) Published on 0 October 03 www.researchmathsci.org Annals of Fuzzy Inventory Model for Imperfect Quality Items
More informationCoordinated Replenishments at a Single Stocking Point
Chapter 11 Coordinated Replenishments at a Single Stocking Point 11.1 Advantages and Disadvantages of Coordination Advantages of Coordination 1. Savings on unit purchase costs.. Savings on unit transportation
More informationFlexible Setup Cost and Deterioration of Products in a Supply Chain Model
Int. J. Appl. Comput. Math (2016) 2:25 40 DOI 10.1007/s40819-015-0045-7 OIGINAL AE Flexible Setup Cost and Deterioration of roducts in a Supply Chain Model Biswajit Sarkar 1 Bimal Kumar Sett 2 Gargi oy
More informationResearch Article Investing in Lead-Time Variability Reduction in a Quality-Adjusted Inventory Model with Finite-Range Stochastic Lead-Time
Hindawi Publishing Corporation Journal of Applied Mathematics and Decision Sciences Volume 2008, Article ID 795869, 13 pages doi:10.1155/2008/795869 Research Article Investing in Lead-Time Variability
More informationCHAPTER IX OPTIMIZATION OF INTEGRATED VENDOR-BUYER PRODUCTION INVENTORY MODEL WITH BACKORDERING WITH TRANSPORTATION COST IN AN UNCERTAIN ENVIRONMENT
CHAPTER IX OPTIMIZATION OF INTEGRATED VENDOR-BUYER PRODUCTION INVENTORY MODEL WITH BACKORDERING WITH TRANSPORTATION COST IN AN UNCERTAIN ENVIRONMENT This chapter develops an integrated single-vendor, single-uyer
More informationOptimal production lots for items with imperfect production and screening processes without using derivatives
7 Int. J. anagement and Enterprise Development, Vol. 4, No., 05 Optimal production lots for items with imperfect production and screening processes without using derivatives Hui-ing Teng Department of
More informationResearch Article Optimal Inventory Policy Involving Ordering Cost Reduction, Back-Order Discounts, and Variable Lead Time Demand by Minimax Criterion
Mathematical Problems in Engineering Volume 2009, Article ID 928932, 19 pages doi:10.1155/2009/928932 Research Article Optimal Inventory Policy Involving Ordering Cost Reduction, Back-Order Discounts,
More informationA Comparative Study Between Inventory Followed by Shortages and Shortages Followed by Inventory Under Trade-Credit Policy
Int. J. Appl. Comput. Math 05 :399 46 DOI 0.007/s4089-05-004-z ORIGINAL PAPER A Comparative Study Between Inventory Followed by Shortages Shortages Followed by Inventory Under Trade-Credit Policy S. Khanra
More informationInternational Journal of Supply and Operations Management
International Journal of Supply and Operations Management IJSOM May 08, Volume 5, Issue, pp. 6-8 ISSN-Print: 8-59 ISSN-Online: 8-55 www.ijsom.com The Quadratic Approximation of an Inflationary Bi-objective
More informationDecision Sciences, Vol. 5, No. 1 (January 1974)
Decision Sciences, Vol. 5, No. 1 (January 1974) A PRESENT VALUE FORMULATION OF THE CLASSICAL EOQ PROBLEM* Robert R. Trippi, California State University-San Diego Donald E. Lewin, Joslyn Manufacturing and
More informationAn Alternative Solution Technique of the JIT Lot-Splitting Model for Supply Chain Management
Appl. Math. Inf. Sci. 9 No. 2 583-591 2015) 583 Applied Mathematics & Information Sciences An International Journal http://dx.doi.org/10.12785/amis/090205 An Alternative Solution Technique of the JIT Lot-Splitting
More informationDecision Science Letters
Decision Science Letters 5 (2016) 45 60 Contents lists available at GrowingScience Decision Science Letters homepage: www.growingscience.com/dsl Credit financing for deteriorating imperfect quality items
More informationCOMPUTATIONAL PROCEDURE OF OPTIMAL INVENTORY MODEL INVOLVING CONTROLLABLE BACKORDER DISCOUNTS AND VARIABLE LEAD TIME WITH DEFECTIVE UNITS
International Journal of Innovative Computing, Information and Control ICIC International c 01 ISSN 1349-4198 Volume 8, Number 1, December 01 pp. 8455 847 COMPUTATIONA PROCEDURE OF OPTIMA INVENTORY MODE
More informationEOQ Model for Weibull Deteriorating Items with Linear Demand under Permissable Delay in Payments
International Journal of Computational Science and Mathematics. ISSN 0974-389 Volume 4, Number 3 (0), pp. 75-85 International Research Publication House http://www.irphouse.com EOQ Model for Weibull Deteriorating
More informationChapter 2 Analysis of Pull Postponement by EOQ-based Models
Chapter 2 Analysis of Pull Postponement by EOQ-based Models A number of quantitative models for analyzing postponement based upon cost and time evaluation have been discussed in the literature. Most of
More informationTHIELE CENTRE. The M/M/1 queue with inventory, lost sale and general lead times. Mohammad Saffari, Søren Asmussen and Rasoul Haji
THIELE CENTRE for applied mathematics in natural science The M/M/1 queue with inventory, lost sale and general lead times Mohammad Saffari, Søren Asmussen and Rasoul Haji Research Report No. 11 September
More informationAn Inventory Model for Time Dependent Deteriorating Items and Holding Cost under Inflations When Vendor Credits To Order Quantity
International Journal of Engineering Research and Development e-issn: 78-07X, p-issn: 78-800X, www.ijerd.com Volume 5, Issue 1 (February 013), PP. 01-09 An Inventory Model for ime Dependent Deteriorating
More informationAn EOQ Model with Certain Uncertainties When Payment Periods are Offered
International Journal of Computational and Applied Mathematics. ISSN 1819-4966 Volume 12, Number 2 (217), pp. 365-389 Research India Publications http://www.ripublication.com An EOQ Model with Certain
More informationResearch Article Technical Note on Q, r, L Inventory Model with Defective Items
Hindawi Publishing Corporation Abstract and Applied Analysis Volume 010, Article ID 878645, 8 pages doi:10.1155/010/878645 Research Article Technical Note on Q, r, L Inventory Model with Defective Items
More informationII. LITERATURE SURVEY
Fuzzy Inventory Model with Shortages under Fully Backlogged Using Signed Distance Method S.K. Indrajitsingha 1, P.N. Samanta, U.K. Misra 3 1 DST INSPIRE Fellow 1, P.G Department of Mathematics, Berhampur
More informationAn application of fuzzy set theory for supply chain coordination
ISSN 1750-9653, England, UK International Journal of Management Science and Engineering Management Vol. 3 (2008) No. 1, pp. 19-32 An application of fuzzy set theory for supply chain coordination Santanu
More informationMaximum-Profit Inventory Model with Stock-Dependent Demand, Time-Dependent Holding Cost, and All-Units Quantity Discounts
Mathematical Modelling and Analysis Publisher: Taylor&Francis and VGTU Volume 20 Number 6, November 2015, 715 736 http://www.tandfonline.com/tmma http://dx.doi.org/10.3846/13926292.2015.1108936 ISSN: 1392-6292
More informationInternational Journal of Industrial Engineering Computations
International Journal of Industrial Engineering Computations 5 (4) 7 38 Contents lists available at GrowingScience International Journal of Industrial Engineering Computations homepage: www.growingscience.com/ijiec
More informationAPPLYING SIGNED DISTANCE METHOD FOR FUZZY INVENTORY WITHOUT BACKORDER. Huey-Ming Lee 1 and Lily Lin 2 1 Department of Information Management
International Journal of Innovative Computing, Information and Control ICIC International c 2011 ISSN 1349-4198 Volume 7, Number 6, June 2011 pp. 3523 3531 APPLYING SIGNED DISTANCE METHOD FOR FUZZY INVENTORY
More informationAn EOQ model for weibull distribution deterioration with time-dependent cubic demand and backlogging
IOP Conference Series: Materials Science and Engineering PAPER OPEN ACCESS An EOQ model for weibull distribution deterioration with time-dependent cubic demand and backlogging To cite this article: G Santhi
More informationAn Alternative Fuzzy EOQ Model with Backlogging for Selling Price and Promotional Effort Sensitive Demand
Int. J. Appl. Comput. Math (2015) 1:69 86 DOI 10.1007/s40819-014-0010-x ORIGINA PAPER An Alternative Fuzzy EOQ Model with Backlogging for Selling Price and Promotional Effort Sensitive Demand Sujit Kumar
More informationIntegrating Quality and Inspection for the Optimal Lot-sizing Problem with Rework, Minimal Repair and Inspection Time
Proceedings of the 2011 International Conference on Industrial Engineering and Operations Management Kuala Lumpur, Malaysia, January 22 24, 2011 Integrating Quality and Inspection for the Optimal Lot-sizing
More informationAN EOQ MODEL FOR TWO-WAREHOUSE WITH DETERIORATING ITEMS, PERIODIC TIME DEPENDENT DEMAND AND SHORTAGES
IJMS, Vol., No. 3-4, (July-December 0), pp. 379-39 Serials Publications ISSN: 097-754X AN EOQ MODEL FOR TWO-WAREHOUSE WITH DETERIORATING ITEMS, PERIODIC TIME DEPENDENT DEMAND AND SHORTAGES Karabi Dutta
More informationRetailer s Optimal Ordering Policy for Deteriorating Items with Ramp-Type Demand under Stock-Dependent Consumption Rate
Information and Management Sciences Volume 19, Number 2, pp. 245-262, 28 Retailer s Optimal Ordering Policy for Deteriorating Items with Ramp-Type Demand under Stock-Dependent Consumption Rate Kun-Shan
More informationCost models for lot streaming in a multistage flow shop
Omega 33 2005) 435 450 www.elsevier.com/locate/omega Cost models for lot streaming in a multistage flow shop Huan Neng Chiu, Jen Huei Chang Department of Industrial Management, National Taiwan University
More informationFUZZY CONTINUOUS REVIEW INVENTORY MODEL WITHOUT BACKORDER FOR DETERIORATING ITEMS. Ajanta Roy *, G.P. Samanta
Electronic Journal of Applied Statistical Analysis EJASA, Electron. J. App. Stat. Anal. Vol., Issue 1 (9), 58 66 ISSN 7-5948, DOI 1.185/i75948vn1p58 8 Università del Salento SIBA http://siba-ese.unile.it/index.php/ejasa/index
More informationMulti level inventory management decisions with transportation cost consideration in fuzzy environment. W. Ritha, S.
Annals of Fuzzy Mathematics and Informatics Volume 2, No. 2, October 2011, pp. 171-181 ISSN 2093 9310 http://www.afmi.or.kr @FMI c Kyung Moon Sa Co. http://www.kyungmoon.com Multi level inventory management
More informationCENTER FOR MULTIMODAL SOLUTIONS FOR CONGESTION MITIGATION (CMS)
Final Report to the CENTER FOR MULTIMODAL SOLUTIONS FOR CONGESTION MITIGATION (CMS) CMS Project Number: 2011-023 Project Title: The Impacts of Freight Mode Splitting on Congestion, Risk, and Delivery Reliability
More informationA Two-Warehouse Inventory Model with Quantity Discounts and Maintenance Actions under Imperfect Production Processes
Appl. Math. Inf. Sci. 9, No. 5, 493-505 (015) 493 Applied Mathematics & Information Sciences An International Journal http://dx.doi.org/10.1785/amis/090533 A Two-Warehouse Inventory Model with Quantity
More informationAn EOQ Model with Time Dependent Weibull Deterioration, Quadratic Demand and Partial Backlogging
Int. J. Appl. Comput. Math (06) :545 56 DOI 0.007/s4089-05-0077-z ORIGINAL PAPER An EOQ Model with Time Dependent Weibull Deterioration, Quadratic Demand and Partial Backlogging Umakanta Mishra Published
More informationDynamic Pricing for Non-Perishable Products with Demand Learning
Dynamic Pricing for Non-Perishable Products with Demand Learning Victor F. Araman Stern School of Business New York University René A. Caldentey DIMACS Workshop on Yield Management and Dynamic Pricing
More informationResearch Article An Optimal Returned Policy for a Reverse Logistics Inventory Model with Backorders
Advances in Decision Sciences Volume 212, Article ID 386598, 21 pages doi:1.1155/212/386598 Research Article An Optimal Returned Policy for a Reverse Logistics Inventory Model with Backorders S. R. Singh
More informationproblem. max Both k (0) and h (0) are given at time 0. (a) Write down the Hamilton-Jacobi-Bellman (HJB) Equation in the dynamic programming
1. Endogenous Growth with Human Capital Consider the following endogenous growth model with both physical capital (k (t)) and human capital (h (t)) in continuous time. The representative household solves
More information2 Functions and Their
CHAPTER Functions and Their Applications Chapter Outline Introduction The Concept of a Function Types of Functions Roots (Zeros) of a Function Some Useful Functions in Business and Economics Equilibrium
More informationA TANDEM QUEUEING SYSTEM WITH APPLICATIONS TO PRICING STRATEGY. Wai-Ki Ching. Tang Li. Sin-Man Choi. Issic K.C. Leung
Manuscript submitted to AIMS Journals Volume X, Number 0X, XX 00X Website: http://aimsciences.org pp. X XX A TANDEM QUEUEING SYSTEM WITH APPLICATIONS TO PRICING STRATEGY WAI-KI CHING SIN-MAN CHOI TANG
More informationAn optimal policy for a single-vendor single-buyer integrated production}inventory system with capacity constraint of the transport equipment
Int. J. Production Economics 65 (2000) 305}315 Technical Note An optimal policy f a single-vend single-buyer integrated production}inventy system with capacity constraint of the transpt equipment M.A.
More informationCompetitive Equilibrium and the Welfare Theorems
Competitive Equilibrium and the Welfare Theorems Craig Burnside Duke University September 2010 Craig Burnside (Duke University) Competitive Equilibrium September 2010 1 / 32 Competitive Equilibrium and
More informationAn easy approach to derive EOQ and EPQ models with shortage and. defective items
An easy approach to derive EOQ and EPQ models with shortage and defective items Hsin-Fan Chen 1, Yung-Fu Huang,*, Yu-Cheng Tu 3 and Ming-Hon Hwang 4 1,,3,4 Department of Mareting and Logistics Management,
More informationNon-Linear Optimization
Non-Linear Optimization Distinguishing Features Common Examples EOQ Balancing Risks Minimizing Risk 15.057 Spring 03 Vande Vate 1 Hierarchy of Models Network Flows Linear Programs Mixed Integer Linear
More informationOn spare parts optimization
On spare parts optimization Krister Svanberg Optimization and Systems Theory, KTH, Stockholm, Sweden. krille@math.kth.se This manuscript deals with some mathematical optimization models for multi-level
More informationResearch Article A Deterministic Inventory Model of Deteriorating Items with Two Rates of Production, Shortages, and Variable Production Cycle
International Scholarly Research Network ISRN Applied Mathematics Volume 011, Article ID 657464, 16 pages doi:10.540/011/657464 Research Article A Deterministic Inventory Model of Deteriorating Items with
More informationCalculation exercise 1 MRP, JIT, TOC and SOP. Dr Jussi Heikkilä
Calculation exercise 1 MRP, JIT, TOC and SOP Dr Jussi Heikkilä Problem 1: MRP in XYZ Company fixed lot size Item A Period 1 2 3 4 5 6 7 8 9 10 Gross requirements 71 46 49 55 52 47 51 48 56 51 Scheduled
More informationSYMBIOSIS CENTRE FOR DISTANCE LEARNING (SCDL) Subject: production and operations management
Sample Questions: Section I: Subjective Questions 1. What are the inputs required to plan a master production schedule? 2. What are the different operations schedule types based on time and applications?
More informationAdvances in Continuous Replenishment Systems. Edmund W. Schuster. Massachusetts Institute of Technology
Advances in Continuous Replenishment Systems Edmund W. Schuster Massachusetts Institute of Technology TRADITIONAL REPLENISHMENT SYSTEM DEMAND FLOW SUPPLIER DISTRIBUTOR WAREHOUSE RETAIL STORES CONSUMER
More informationCHAPTER-3 MULTI-OBJECTIVE SUPPLY CHAIN NETWORK PROBLEM
CHAPTER-3 MULTI-OBJECTIVE SUPPLY CHAIN NETWORK PROBLEM 3.1 Introduction A supply chain consists of parties involved, directly or indirectly, in fulfilling customer s request. The supply chain includes
More informationEOQ Model For Deteriorating Items Under Two And Three Parameter Weibull Distribution And Constant IHC With Partially Backlogged Shortages
International Journal of Science, Engineering and Technology Research (IJSETR), Volume 4, Issue 0, October 205 EOQ Model For Deteriorating Items Under Two And Three Parameter Weibull Distribution And Constant
More informationImproving Supply Chain Performance: Real-Time Demand Information and Flexible Deliveries
Improving Supply Chain Performance: Real-Time Demand Information and Flexible Deliveries Kevin H. Shang Sean X. Zhou Geert-Jan van Houtum The Fuqua School of Business, Duke University, Durham, North Carolina
More informationResearch Article Batch Scheduling on Two-Machine Flowshop with Machine-Dependent Setup Times
Advances in Operations Research Volume 2009, Article ID 153910, 10 pages doi:10.1155/2009/153910 Research Article Batch Scheduling on Two-Machine Flowshop with Machine-Dependent Setup Times Lika Ben-Dati,
More informationISyE 6201: Manufacturing Systems Instructor: Spyros Reveliotis Spring 2006 Solutions to Homework 1
ISyE 601: Manufacturing Systems Instructor: Spyros Reveliotis Spring 006 Solutions to Homework 1 A. Chapter, Problem 4. (a) D = 60 units/wk 5 wk/yr = 310 units/yr h = ic = 0.5/yr $0.0 = $0.005/ yr A =
More informationThe Single and Multi-Item Transshipment Problem with Fixed Transshipment Costs
The Single and Multi-Item Transshipment Problem with Fixed Transshipment Costs Reut Noham, Michal Tzur Department of Industrial Engineering, Tel-Aviv University, Tel Aviv, Israel Received 1 October 2013;
More informationAn Optimal Rotational Cyclic Policy for a Supply Chain System with Imperfect Matching Inventory and JIT Delivery
Proceedings of the 010 International onference on Industrial Engineering and Operations Management Dhaa, Bangladesh, January 9 10, 010 An Optimal Rotational yclic Policy for a Supply hain System with Imperfect
More information2001, Dennis Bricker Dept of Industrial Engineering The University of Iowa. DP: Producing 2 items page 1
Consider a production facility which can be devoted in each period to one of two products. For simplicity, we assume that the production rate is deterministic and that production is always at full capacity.
More informationAn EOQ Model with Temporary Stock Dependent Demand with Random Lag
International Journal of Computer Science & Communication Vol. 1, No., July-December 010, pp. 43-47 An EOQ Model with Temporary Stock Dependent Demand with Random Lag P.S.R.K.Prasad 1 & K.V.S.Sarma 1 Narayana
More informationOptimal Control of an Inventory System with Joint Production and Pricing Decisions
Optimal Control of an Inventory System with Joint Production and Pricing Decisions Ping Cao, Jingui Xie Abstract In this study, we consider a stochastic inventory system in which the objective of the manufacturer
More informationA New Algorithm and a New Heuristic for Serial Supply Systems.
A New Algorithm and a New Heuristic for Serial Supply Systems. Guillermo Gallego Department of Industrial Engineering and Operations Research Columbia University Özalp Özer Department of Management Science
More informationStochastic inventory system with two types of services
Int. J. Adv. Appl. Math. and Mech. 2() (204) 20-27 ISSN: 2347-2529 Available online at www.ijaamm.com International Journal of Advances in Applied Mathematics and Mechanics Stochastic inventory system
More informationFinite-horizon operations planning for a lean supply chain system
Louisiana State University LSU Digital Commons LSU Doctoral Dissertations Graduate School 2003 Finite-horizon operations planning for a lean supply chain system Ahmad Diponegoro Louisiana State University
More informationPractice Questions for Math 131 Exam # 1
Practice Questions for Math 131 Exam # 1 1) A company produces a product for which the variable cost per unit is $3.50 and fixed cost 1) is $20,000 per year. Next year, the company wants the total cost
More informationEffect of repair cost on the rework decision-making in an economic production quantity model
Effect of repair cost on the rework decision-making in an economic production quantity model Singa Wang Chiu Department of Business Administration Chaoyang University of Technology 68, Gifeng E. Rd. Wufeng,
More informationDETERMINATION OF OPTIMAL ORDER QUANTITY OF INTEGRATED AN INVENTORY MODEL USING YAGER RANKING METHOD
International Journal of Physics and Mathematical Sciences ISSN: 77- (Online) An Online International Journal Aailale at http://www.citech.org/jpms.htm 03 Vol. 3 () January-March, pp.73-80/ritha and SSA
More informationAdvanced Macroeconomics
Advanced Macroeconomics The Ramsey Model Marcin Kolasa Warsaw School of Economics Marcin Kolasa (WSE) Ad. Macro - Ramsey model 1 / 30 Introduction Authors: Frank Ramsey (1928), David Cass (1965) and Tjalling
More informationMarkov Chains. Chapter 16. Markov Chains - 1
Markov Chains Chapter 16 Markov Chains - 1 Why Study Markov Chains? Decision Analysis focuses on decision making in the face of uncertainty about one future event. However, many decisions need to consider
More informationAn Order Quantity Decision System for the Case of Approximately Level Demand
Capter 5 An Order Quantity Decision System for te Case of Approximately Level Demand Demand Properties Inventory problems exist only because tere are demands; oterwise, we ave no inventory problems. Inventory
More informationh Edition Money in Search Equilibrium
In the Name of God Sharif University of Technology Graduate School of Management and Economics Money in Search Equilibrium Diamond (1984) Navid Raeesi Spring 2014 Page 1 Introduction: Markets with Search
More informationSupply planning optimization for linear production system with stochastic lead-times and quality control
Supply planning optimization for linear production system with stochastic lead-times and quality control O Ben Ammar, B Bettayeb, Alexandre Dolgui To cite this version: O Ben Ammar, B Bettayeb, Alexandre
More informationPART III. INVENTORY THEORY
PART III Part I: Markov chains PART III. INVENTORY THEORY is a research field within operations research that finds optimal design of inventory systems both from spatial as well as temporal point of view
More informationJOINT PRICING AND PRODUCTION PLANNING FOR FIXED PRICED MULTIPLE PRODUCTS WITH BACKORDERS. Lou Caccetta and Elham Mardaneh
JOURNAL OF INDUSTRIAL AND doi:10.3934/jimo.2010.6.123 MANAGEMENT OPTIMIZATION Volume 6, Number 1, February 2010 pp. 123 147 JOINT PRICING AND PRODUCTION PLANNING FOR FIXED PRICED MULTIPLE PRODUCTS WITH
More informationOptimal and Heuristic Echelon ( r, nq, T ) Policies in Serial Inventory Systems with Fixed Costs
OPERATIONS RESEARCH Vol. 58, No. 2, March April 2010, pp. 414 427 issn 0030-364X eissn 1526-5463 10 5802 0414 informs doi 10.1287/opre.1090.0734 2010 INFORMS Optimal and Heuristic Echelon ( r, nq, T )
More informationOptimal ordering policies for periodic-review systems with replenishment cycles
European Journal of Operational Research 17 (26) 44 56 Production, Manufacturing and Logistics Optimal ordering policies for periodic-review systems with replenishment cycles Chi Chiang * Department of
More informationOrdering Policies for Periodic-Review Inventory Systems with Quantity-Dependent Fixed Costs
OPERATIONS RESEARCH Vol. 60, No. 4, July August 2012, pp. 785 796 ISSN 0030-364X (print) ISSN 1526-5463 (online) http://dx.doi.org/10.1287/opre.1110.1033 2012 INFORMS Ordering Policies for Periodic-Review
More informationProduction Inventory Model with Different Deterioration Rates Under Linear Demand
IOSR Journal of Engineering (IOSRJEN) ISSN (e): 50-0, ISSN (p): 78-879 Vol. 06, Issue 0 (February. 06), V PP 7-75 www.iosrjen.org Production Inventory Model with Different Deterioration Rates Under Linear
More informationMATH 445/545 Homework 1: Due February 11th, 2016
MATH 445/545 Homework 1: Due February 11th, 2016 Answer the following questions Please type your solutions and include the questions and all graphics if needed with the solution 1 A business executive
More informationInfluence of product return lead-time on inventory control
Influence of product return lead-time on inventory control Mohamed Hichem Zerhouni, Jean-Philippe Gayon, Yannick Frein To cite this version: Mohamed Hichem Zerhouni, Jean-Philippe Gayon, Yannick Frein.
More informationCoordinating Inventory Control and Pricing Strategies with Random Demand and Fixed Ordering Cost: The Finite Horizon Case
OPERATIONS RESEARCH Vol. 52, No. 6, November December 2004, pp. 887 896 issn 0030-364X eissn 1526-5463 04 5206 0887 informs doi 10.1287/opre.1040.0127 2004 INFORMS Coordinating Inventory Control Pricing
More informationLecture 2: Firms, Jobs and Policy
Lecture 2: Firms, Jobs and Policy Economics 522 Esteban Rossi-Hansberg Princeton University Spring 2014 ERH (Princeton University ) Lecture 2: Firms, Jobs and Policy Spring 2014 1 / 34 Restuccia and Rogerson
More informationOptimal Run Time for EMQ Model with Backordering, Failure-In- Rework and Breakdown Happening in Stock-Piling Time
Optimal Run Time for EMQ Model with Backordering, Failure-In- Rework and Breakdown Happening in Stock-Piling Time YUAN-SHYI PETER CHIU, SHUN-SHENG WANG, CHIA-KUAN TING*, HSIEN-JU CHUANG, YU-LUNG LIEN Department
More informationTHE COMPLETE SOLUTION PROCEDURE FOR THE FUZZY EOQ INVENTORY MODEL WITH LINEAR AND FIXED BACK ORDER COST
Aryabatta Journal of Matematics & Informatics Vol. 5, No., July-ec., 03, ISSN : 0975-739 Journal Impact Factor (0) : 0.93 THE COMPLETE SOLUTION PROCEURE FOR THE FUZZY EOQ INVENTORY MOEL WITH LINEAR AN
More informationMixture Distributions for Modeling Lead Time Demand in Coordinated Supply Chains. Barry Cobb. Alan Johnson
Mixture Distributions for Modeling Lead Time Demand in Coordinated Supply Chains Barry Cobb Virginia Military Institute Alan Johnson Air Force Institute of Technology AFCEA Acquisition Research Symposium
More informationResearch Article Mathematical Programming Approach to the Optimality of the Solution for Deterministic Inventory Models with Partial Backordering
Advances in Operations Research Volume 013, Article ID 7648, 7 pages http://dx.doi.org/10.1155/013/7648 Research Article Mathematical Programming Approach to the Optimality of the Solution for Deterministic
More informationThis paper studies the optimization of the S T inventory policy, where T is the replenishment interval and S
MANUFACTURING & SERVICE OPERATIONS MANAGEMENT Vol. 14, No. 1, Winter 2012, pp. 42 49 ISSN 1523-4614 (print) ISSN 1526-5498 (online) http://dx.doi.org/10.1287/msom.1110.0353 2012 INFORMS Good and Bad News
More informationGlobal and China Sodium Silicate Industry 2014 Market Research Report
2014 QY Research Reports Global and China Sodium Silicate Industry 2014 Market Research Report QY Research Reports included market size, share & analysis trends on Global and China Sodium Silicate Industry
More informationFuzzy Inventory Control Problem With Weibull Deterioration Rate and Logarithmic Demand Rate
Volume 7 No. 07, 5-44 ISSN: -8080 (printed version); ISSN: 4-95 (on-line version) url: http://www.ijpam.eu ijpam.eu Fuzzy Inventory Control Problem With Weibull Deterioration Rate and Logarithmic Demand
More informationCost and Preference in Recommender Systems Junhua Chen LESS IS MORE
Cost and Preference in Recommender Systems Junhua Chen, Big Data Research Center, UESTC Email:junmshao@uestc.edu.cn http://staff.uestc.edu.cn/shaojunming Abstract In many recommender systems (RS), user
More informationFuzzy Inventory Model for Deteriorating Items with Time Dependent Demand and Partial Backlogging
Applied Mathematics, 05, 6, 496-509 Published Online March 05 in SciRes. http://www.scirp.org/journal/am http://dx.doi.org/0.46/am.05.6047 Fuzzy Inventory Model for Deteriorating Items with ime Dependent
More informationAn Enhance PSO Based Approach for Solving Economical Ordered Quantity (EOQ) Problem
International OPEN ACCESS Journal Of Modern Engineering Research (IJMER) An Enhance PSO Based Approach for Solving Economical Ordered Quantity (EOQ) Problem Ashutosh Khare, Dr. B. B. Singh 2, Shalini khare
More informationA Supply Chain Design Model with Unreliable Supply
Missouri University of Science and Technology Scholars' Mine Business and Information Technology Faculty Research & Creative Works Business and Information Technology 8-17-2007 A Supply Chain Design Model
More informationSupply Chain Network Competition in Price and Quality with Multiple Manufacturers and Freight Service Providers
Supply Chain Network Competition in Price and Quality with Multiple Manufacturers and Freight Service Providers Anna Nagurney Sara Saberi Department of Operations and Information Management University
More informationLecture 2 The Centralized Economy
Lecture 2 The Centralized Economy Economics 5118 Macroeconomic Theory Kam Yu Winter 2013 Outline 1 Introduction 2 The Basic DGE Closed Economy 3 Golden Rule Solution 4 Optimal Solution The Euler Equation
More informationPart A. Ch (a) Thus, order quantity is 39-12=27. (b) Now b=5. Thus, order quantity is 29-12=17
Homework2Solution Part A. Ch 2 12 (a) b = 65 40 = 25 from normal distribution table Thus, order quantity is 39-12=27 (b) Now b=5 from normal distribution table Thus, order quantity is 29-12=17 It is interesting
More information