Production Inventory Model with Different Deterioration Rates Under Linear Demand

Similar documents
Production Inventory Model with Different Deterioration Rates Under Shortages and Linear Demand

Inventory Management of Time Dependent. Deteriorating Items with Salvage Value

EOQ Model for Weibull Deteriorating Items with Linear Demand under Permissable Delay in Payments

An Inventory Model for Gompertz Distribution Deterioration Rate with Ramp Type Demand Rate and Shortages

Retailer s Optimal Ordering Policy for Deteriorating Items with Ramp-Type Demand under Stock-Dependent Consumption Rate

An Inventory Model for Time Dependent Deteriorating Items and Holding Cost under Inflations When Vendor Credits To Order Quantity

Research Article A Deterministic Inventory Model of Deteriorating Items with Two Rates of Production, Shortages, and Variable Production Cycle

EOQ Model For Deteriorating Items Under Two And Three Parameter Weibull Distribution And Constant IHC With Partially Backlogged Shortages

An EPQ Model of Deteriorating Items using Three Parameter Weibull Distribution with Constant Production Rate and Time Varying Holding Cost"

An EOQ model for weibull distribution deterioration with time-dependent cubic demand and backlogging

An EOQ Model with Time Dependent Weibull Deterioration, Quadratic Demand and Partial Backlogging

An EOQ Model with Temporary Stock Dependent Demand with Random Lag

Fuzzy Inventory Model for Deteriorating Items with Time Dependent Demand and Partial Backlogging

Decision Science Letters

International Journal of Industrial Engineering Computations

Chapter 2 Analysis of Pull Postponement by EOQ-based Models

7.1 INTRODUCTION. In this era of extreme competition, each subsystem in different

Optimal lot sizing for deteriorating items with expiration date

FUZZY CONTINUOUS REVIEW INVENTORY MODEL WITHOUT BACKORDER FOR DETERIORATING ITEMS. Ajanta Roy *, G.P. Samanta

II. LITERATURE SURVEY

Research Article A Partial Backlogging Inventory Model for Deteriorating Items with Fluctuating Selling Price and Purchasing Cost

An EOQ Model with Certain Uncertainties When Payment Periods are Offered

A Comparative Study Between Inventory Followed by Shortages and Shortages Followed by Inventory Under Trade-Credit Policy

Maximum-Profit Inventory Model with Stock-Dependent Demand, Time-Dependent Holding Cost, and All-Units Quantity Discounts

Integrating Quality and Inspection for the Optimal Lot-sizing Problem with Rework, Minimal Repair and Inspection Time

AN EOQ MODEL FOR TWO-WAREHOUSE WITH DETERIORATING ITEMS, PERIODIC TIME DEPENDENT DEMAND AND SHORTAGES

2. Assumptions and Notation

An Integrated Just-In-Time Inventory System with Stock-Dependent Demand

Dr.Pravat Kumar Sukla P.S College, Koksara,Kalahandi,Odisa,INDIA

Fuzzy Inventory Model for Imperfect Quality Items with Shortages

An Alternative Fuzzy EOQ Model with Backlogging for Selling Price and Promotional Effort Sensitive Demand

Fuzzy Inventory Control Problem With Weibull Deterioration Rate and Logarithmic Demand Rate

OPTIMAL CONTROL OF A PRODUCTION SYSTEM WITH INVENTORY-LEVEL-DEPENDENT DEMAND

Flexible Setup Cost and Deterioration of Products in a Supply Chain Model

Research Article Limit Distribution of Inventory Level of Perishable Inventory Model

Optimal production lots for items with imperfect production and screening processes without using derivatives

REVIEW PERIOD REORDER POINT PROBABILISTIC INVENTORY SYSTEM FOR DETERIORATING ITEMS WITH THE MIXTURE OF BACKORDERS AND LOST SALES

Neutrosophic EOQ Model with Price Break

Research Article An EPQ Model for Deteriorating Production System and Items with Rework

Research Article International Journals of Advanced Research in Computer Science and Software Engineering ISSN: X (Volume-7, Issue-6)

Multi level inventory management decisions with transportation cost consideration in fuzzy environment. W. Ritha, S.

Buyer - Vendor incentive inventory model with fixed lifetime product with fixed and linear back orders

A Partially Backlogging Inventory Model for Deteriorating Items with Ramp Type Demand Rate

An Enhance PSO Based Approach for Solving Economical Ordered Quantity (EOQ) Problem

Coordinated Replenishments at a Single Stocking Point

PAijpam.eu ON FUZZY INVENTORY MODEL WITH ALLOWABLE SHORTAGE

An inventory model with shortages for imperfect items using substitution of two products

CHAPTER IX OPTIMIZATION OF INTEGRATED VENDOR-BUYER PRODUCTION INVENTORY MODEL WITH BACKORDERING WITH TRANSPORTATION COST IN AN UNCERTAIN ENVIRONMENT

Research Article An Optimal Returned Policy for a Reverse Logistics Inventory Model with Backorders

A Fuzzy Inventory Model. Without Shortages Using. Triangular Fuzzy Number

An Inventory Model for Two Warehouses with Constant Deterioration and Quadratic Demand Rate under Inflation and Permissible Delay in Payments

Key words: EOQ, Deterioration, Stock dependent demand pattern

MA 181 Lecture Chapter 7 College Algebra and Calculus by Larson/Hodgkins Limits and Derivatives

An Inventory Model for Time Dependent Weibull Deterioration with Partial Backlogging

International Journal of Supply and Operations Management

An Inventory Model for Constant Deteriorating Items with Price Dependent Demand and Time-varying Holding Cost

Study of Memory Effect in an Inventory Model. with Quadratic Type Demand Rate and. Salvage Value

Q3) a) Explain the construction of np chart. b) Write a note on natural tolerance limits and specification limits.

Decision Sciences, Vol. 5, No. 1 (January 1974)

Deteriorating Inventory Model with Time. Dependent Demand and Partial Backlogging

An Integrated Inventory Model with Geometric Shipment Policy and Trade-Credit Financing under Stochastic Lead Time

Stocking Retail Assortments Under Dynamic Consumer Substitution

Replenishment Planning for Stochastic Inventory System with Shortage Cost

2 Functions and Their

Production Planning and Control

UNIT-4 Chapter6 Linear Programming

Inventory optimization of distribution networks with discrete-event processes by vendor-managed policies

Keywords:- Economic Ordered Quantity (EOQ) problem, PSO, Chaotic Maps, Logistic Map, Lozi Map.

A single server perishable inventory system with N additional options for service. Jeganathan Kathirvel

An easy approach to derive EOQ and EPQ models with shortage and. defective items

An application of fuzzy set theory for supply chain coordination

On a Discrete-In-Time Order Level Inventory Model for Items with Random Deterioration

Computers and Mathematics with Applications. An EOQ model of homogeneous products while demand is salesmen s initiatives and stock sensitive

Math 1325 Final Exam Review. (Set it up, but do not simplify) lim

Worst case analysis for a general class of on-line lot-sizing heuristics

Optimal Run Time for EMQ Model with Backordering, Failure-In- Rework and Breakdown Happening in Stock-Piling Time

M.Sc. (Final) DEGREE EXAMINATION, MAY Final Year. Statistics. Paper I STATISTICAL QUALITY CONTROL. Answer any FIVE questions.

I Time Allowed : Three Hours I I Maximum Marks

Technical Companion to: Sharing Aggregate Inventory Information with Customers: Strategic Cross-selling and Shortage Reduction

M/M/1 Queueing systems with inventory

Manufacturing Lot Sizing with Backordering, Scrap, and Random Breakdown Occurring in Inventory-Stacking Period

Cost-Effective Optimization on a Two Demand Classes Inventory System

Lagrangian Duality. Richard Lusby. Department of Management Engineering Technical University of Denmark

Math 1314 Lesson 24 Maxima and Minima of Functions of Several Variables

2001, Dennis Bricker Dept of Industrial Engineering The University of Iowa. DP: Producing 2 items page 1

ASSIGNMENT - 1 M.Sc. DEGREE EXAMINATION, MAY 2019 Second Year STATISTICS. Statistical Quality Control MAXIMUM : 30 MARKS ANSWER ALL QUESTIONS

A Non-Random Optimization Approach to a Disposal Mechanism Under Flexibility and Reliability Criteria

INVENTORY AND TRANSPORTATION COST MINIMIZATION IN THE DELIVERY LOGISTICS OF SWINE FLU VACCINE

Two Heterogeneous Servers Queueing-Inventory System with Sharing Finite Buffer and a Flexible Server

International OPEN ACCESS Journal Of Modern Engineering Research (IJMER)

Spring 2018 IE 102. Operations Research and Mathematical Programming Part 2

International Journal of Computer Science Trends and Technology (IJCST) Volume 3 Issue 6, Nov-Dec 2015

MS-E2140. Lecture 1. (course book chapters )

SECTION 5.1: Polynomials

Modified Kaptur s Measures of Entropy and Directed Divergence on Imposition of Inequality Constraints on Probabilities

Mixture inventory model in fuzzy demand with controllable lead time

LINEAR RETRIAL INVENTORY SYSTEM WITH SECOND OPTIONAL SERVICE UNDER MIXED PRIORITY SERVICE

Replenishment Decision Making with Permissible Shortage, Repairable Nonconforming Products and Random Equipment Failure

THIELE CENTRE. The M/M/1 queue with inventory, lost sale and general lead times. Mohammad Saffari, Søren Asmussen and Rasoul Haji

IE 495 Final Exam. Due Date: May 1, 2003

Transcription:

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 Demand S.R. Sheikh, Raman Patel Department of Statistics, V.B. Shah Institute of Management, Amroli, Surat, INDIA Raman Patel, Department of Statistics,Veer Narmad South Gujarat University, Surat, INDIA Abstract:- A production inventory model with linear trend in demand is developed. Different deterioration rates are considered in a cycle. Shortages not allowed. o illustrate the model numerical example is provided and sensitivity analysis is also carried out for parameters. Key Words: Production, Inventory model, Varying Deterioration, Linear demand, ime varying holding cost I. INRODUCION he basic question for making a production inventory model is how much to produce to satisfy customer demand. So, the problem is to find the optimal time to maximize the total relevant profit. Moreover, deterioration of certain items occurs due to spoilage, obsolescence, evaporation, etc. Many authors in past studied inventory model for deteriorating items. Covert and Philip [] derived an EOQ model for items with weibull distribution deterioration. Mishra [7] developed the EPQ model for deteriorating items with varying and constant rate of deterioration. Aggarwal [] discussed an order level inventory model with constant rate of deterioration. Gupta and Vrat [4] developed an inventory model with stock dependent consumption rate. Mandal and Phaujdar [6] presented an inventory model for stock dependent consumption rate. Haiping and Wang [5] studied an economic policy model for deteriorating items with time proportional demand. Other research work related to deteriorating items can be found in, for instance (Raafat [9], Goyal and Giri [], Ruxian et al. []). Roy and Chaudhary [0] studied a production inventory model for deteriorating items when demand rate is inventory level dependent and production rate depends both on stock level and demand. ripathy and Mishra [] developed an order level inventory model with time dependent Weibull deterioration and ramp type demand rate where production and demand were time dependent. Patel and Patel [8] developed a deteriorating items production inventory model with demand dependent production rate. Initially there is no deterioration in most of the products. After certain time deterioration starts and again after certain time the rate of deterioration increases with time. Here we have used such a concept and developed the deteriorating items inventory models. In this paper we have developed a production inventory model with different deterioration rates for the cycle time under time varying holding cost. Shortages are not allowed. Numerical example is provided to illustrate the model and sensitivity analysis of the optimal solutions for major parameters is also carried out. II. ASSUMPIONS AND NOAIONS Notations: he following notations are used for the development of the model: P(t) : Production rate is a function of demand ( P(t) = ηd(t), η>0) D(t) : Demand rate is a linear function of time t (a+bt, a>0, 0<b<) A : Replenishment cost per order c : Purchasing cost per unit p : Selling price per unit : Length of inventory cycle I(t) : Inventory level at any instant of time t, 0 t Q : Order quantity θ : Deterioration rate during μ t t, 0< θ< θt : Deterioration rate during, t t, 0< θ< π : otal relevant profit per unit time. Assumptions: he following assumptions are considered for the development of the model: he demand of the product is declining as a linear function of time. Rate of production is a function of demand 7 P a g e

Replenishment rate is infinite and instantaneous. Lead time is zero. Shortages are not allowed. Deteriorated units neither be repaired nor replaced during the cycle time. III. HE MAHEMAICAL MODEL AND ANALYSIS Let I(t) be the inventory at time t (0 t ) as shown in figure. Figure he differential equations which describes the instantaneous states of I(t) over the period (0, ) is given by = (η - )(a + b t), + θ I(t) = (η - )(a + b t), + θ ti(t) = - (a + b t), with initial conditions I(0) = 0, I(μ ) = S, I(t ) = Q and I() = 0. Solutions of these equations are given by I(t) = (η - )(at + b t ). 0 t μ () μ t t () t t () I(t) = S + θ μ - t -(η - ) a μ -t + b μ - t + a θ μ - t + b θ μ -t -a θ t μ -t - b θ t μ -t 4 4 I(t) = a - t + b - t + a θ - t + b θ - t - a θ t - t - b θ t - t. 6 8 4 Putting t = µ in equation (4), we get S = (η - )(aμ + b μ ) Putting t = t in equations (5) and (6), we have I(t ) = S + θ μ - t (4) (5) (by neglecting higher powers of θ) - (η - ) a μ - t + b μ - t + a θ μ - t + b θ μ - t - a θ t μ - t - b θ t μ - t 4 4 I(t ) = a - t + b - t + a θ - t + b θ - t - aθ t - t - b θ t - t. 6 8 4 So, from equations (8) and (9), we have t = S ( + θ μ ) - (η - )aμ - a S θ + η aμ From equation (0), we see that t is a function of μ, and S, so t is not a decision variable. Putting value of S from equation (7) in equation (5), we have (6) (7) (8) (9) (0) 7 P a g e

I(t) = (η - )(a μ + b μ ) + θ μ - t - (η - ) a μ - t + b μ - t + a θ μ - t + b θ μ - t - a θ t μ - t - b θ t μ - t Putting t = t, in equation (5), we get Q = (η - )(a μ + b μ ) + θ μ - t - ( η - ) a μ - t + b μ - t + a θ μ - t + b θ μ - t - a θ t μ - t - b θ t μ - t Based on the assumptions and descriptions of the model, the total annual relevant profit (π), include the following elements: (i) Ordering cost (OC) = A () (ii) H C = 0 (x + yt)i(t)d t μ t = (x + yt)i(t)d t + (x + yt)i(t)d t + (x + yt)i(t)d t 0 μ t = -x a + b + a θ + b θ t + y η b - b μ + x η a -a μ - x - b - aθ - b θ -ya t 6 8 4 4 4 4 + x - b - a θ - b θ -ya -x η a θ μ + η b θ μ - a θ μ - b θ μ μ + x b θ + yaθ 4 6 6 5 8 + x a θ + y - b - a θ - b θ + -x a + y a + b a θ + b θ - x b θ + yaθ t 4 4 6 8 5 8 4 4 4 5 4 + x - η b θ + b θ + y - b + η b + a θ - η a θ t + x η a -a + y η a θ μ + η b θ μ - a θ μ - b θ μ t 4 6 6 6 6 + x η b - b + y η a -a μ 5 - yb θ t - x - η b θ + b θ + y - b + η b + a θ - η a θ μ - x η a -a + y η a θ μ + η b θ μ - a θ μ - b θ μ μ 4 8 4 6 6 6 6 6 4 5 - x - b + η b + a θ - η a θ + y η a -a μ + y - η b θ + b θ t - -x a + y - b - a θ - b θ t 5 6 6 4 +x η a θ μ + η b θ μ - a θ μ - b θ μ t 6 6 + x - b + η b + a θ - η a θ + y η a -a t + x a + b a θ + b θ - y - η b θ + b θ μ + yb θ 6 8 5 6 6 4 8 (iii) t D C = c θ I(t)d t + θ ti(t)d t μ t 4 4 5 6 () () (4) (by neglecting higher powers of θ) η a μ t + η b μ t -a μ t - b μ t + η a θ μ μ t - t + η b θ μ μ t - t -a θ μ μ t - t 4 - bθ μ μ t - t -η a μ t - t - η b μ t - t - η a θ μ t - t - η b θ μ t - t 4 = c θ 4 + η a θ μ t - t + η b θ μ t - t + a μ t - t + b μ t - t + a θ μ t - t 4 4 4 + bθ μ t - t -a θ μ t - t - b θ μ t - t 4 4 7 P a g e

-cθ η a μ + η b μ - a μ - b μ + η a θ μ + η b θ μ - a θ μ - b θ μ 6 6 8 8 4 4 +cθ b θ + a θ + - b - a θ - b θ - a a + b + a θ + bθ 4 8 5 4 4 6 8 6 5 4 4 6 5 - c θ b θ t + a θ t + - b - a θ - b θ t - a t a + b + a θ + b θ t 4 8 5 4 4 6 8 4 4 4 (5) (iv) S R = p (a+ b t)d t = p a + b (6) 0 he total profit (π) during a cycle, consisted of the following: π = S R - O C - H C - D C Substituting values from equations () to (6) in equation (7), we get total profit per unit. Putting µ = v and value of t from equation (0) in equation (7), we get profit in terms of. he optimal value of = * (say), which maximizes profit π can be obtained by differentiating it with respect to and equate it to zero (7) i.e. d π = 0 d provided it satisfies the condition d π < 0. d (8) (9) IV. NUMERICAL EXAMPLE Considering A= Rs.00, a = 500, b=0.05, η=, c=rs. 5, p=rs. 40, θ=0.05, x = Rs. 5, y=0.05, v =0.0, in appropriate units. he optimal value *=0.740 and Profit*= Rs. 947.9465 and optimum order quantity Q*=9.075. he second order condition given in equation (9) is also satisfied. he graphical representation of the concavity of the profit function is also given. and Profit Graph V. SENSIIVIY ANALYSIS On the basis of the data given in example above we have studied the sensitivity analysis by changing the following parameters one at a time and keeping the rest fixed. able Sensitivity Analysis Parameter % Profit Q +0% 0.4 4.0 0.0 a +0% 0.570 447.5640 97.79-0% 0.96 7499.654 88.09-0% 0.468 557.8558 8.885 θ +0% 0.696 9467.890 9.9790 74 P a g e

x A +0% 0.77 9470.8 9.476-0% 0.76 9475.57 9.69-0% 0.786 9478.4 94.56 +0% 0.457 948.095 86.068 +0% 0.590 9450.056 89.444-0% 0.909 9496.864 97.470-0% 0.40 95.8587 0.066 +0% 0.4085 94.84 0.69 +0% 0.97 9446.860 97.4458-0% 0.55 9500.698 88.998-0% 0.55 947.9465 8.566 From the table we observe that as parameter a increases/ decreases average total profit and optimum order quantity also increases/ decreases. Also, we observe that with increase and decrease in the value of θ and x, there is corresponding decrease/ increase in total profit and optimum order quantity. From the table we observe that as parameter A increases/ decreases average total profit decreases/ increases and optimum order quantity increases/ decreases. VI. CONCLUSION In this paper, we have developed a production inventory model for deteriorating items with linear demand with different deterioration rates. Sensitivity with respect to parameters have been carried out. he results show that with the increase/ decrease in the parameter values there is corresponding increase/ decrease in the value of profit. REFERENCES []. Aggarwal, S.P. (978): A note on an order level inventory model for a system with constant rate of deterioration; Opsearch, Vol. 5, pp. 84-87. []. Covert, R.P. and Philip, G.C. (97): An EOQ model for items with Weibull distribution deterioration; AIIE ransactions, Vol. 5, pp. -6. []. Goyal, S.K. and Giri, B. (00): Recent trends in modeling of deteriorating inventory; Euro. J. Oper. Res., Vol. 4, pp. -6. [4]. Gupta, R. and Vrat, P. (986): Inventory model for stock dependent consumption rate, Opsearch, pp. 9-4. [5]. Haiping, U. and Wang, H. (990): An economic ordering policy model for deteriorating items with time proportional demand; Euro. J. Oper.Res., Vol. 46, pp. -7. [6]. Mandal, B.N. and Phujdar, S. (989): A note on inventory model with stock dependent consumption rate; Opsearch, Vol. 6, pp. 4-46. [7]. Mishra, R.B. (975): Optimum production lot size model for a system with deteriorating inventory; International J. Production Research, Vol., pp. 495-505. [8]. Patel, R. and Patel, S. (0): Deteriorating items production inventory model with demand dependent production rate and varying holding cost; Indian J. Mathematics Research, Vol., No., pp. 6-70. [9]. Raafat, F. (99): Survey of literature on continuous deteriorating inventory model, J. of O.R. Soc., Vol. 4, pp. 7-7. [0]. Roy,. and Chaudhary, K.S. (009): A production inventory model under stock dependent demand, Weibull distribution deterioration and shortages; Intl. rans. In Oper. Res., Vol. 6, pp. 5-46. []. Ruxian, L., Hongjie, L. and Mawhinney, J.R. (00): A review on deteriorating inventory study; J. Service Sci. and management; Vol., pp. 7-9. []. ripathy, C.K. and Mishra, U. (0): An EOQ model with time dependent Weibull deterioration and ramp type demand; Inturnational J. of Industrial Engineering and Computations, Vol., pp. 07-8. 75 P a g e