THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 10, Number 2/2009, pp

Similar documents
MULTIOBJECTIVE NONLINEAR FRACTIONAL PROGRAMMING PROBLEMS INVOLVING GENERALIZED d - TYPE-I n -SET FUNCTIONS

OPTIMALITY AND SECOND ORDER DUALITY FOR A CLASS OF QUASI-DIFFERENTIABLE MULTIOBJECTIVE OPTIMIZATION PROBLEM

Available online Journal of Scientific and Engineering Research, 2014, 1(1): Research Article

Continuous Indexed Variable Systems

Comparison of the Bayesian and Maximum Likelihood Estimation for Weibull Distribution

Brownian Motion and Stochastic Calculus. Brownian Motion and Stochastic Calculus

On cartesian product of fuzzy primary -ideals in -LAsemigroups

CONTROLLABILITY OF A CLASS OF SINGULAR SYSTEMS

On the Computation of Optimal Control Problems with Terminal Inequality Constraint via Variation Evolution

Key words: Fractional difference equation, oscillatory solutions,

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables

The Linear Regression Of Weighted Segments

A Remark on Generalized Free Subgroups. of Generalized HNN Groups

Chapter 3: Maximum-Likelihood & Bayesian Parameter Estimation (part 1)

14. Poisson Processes

Density estimation. Density estimations. CS 2750 Machine Learning. Lecture 5. Milos Hauskrecht 5329 Sennott Square

Multiobjective Duality in Variational Problems with Higher Order Derivatives

The algebraic immunity of a class of correlation immune H Boolean functions

FORCED VIBRATION of MDOF SYSTEMS

Upper Bound For Matrix Operators On Some Sequence Spaces

4. Runge-Kutta Formula For Differential Equations

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China,

Random Generalized Bi-linear Mixed Variational-like Inequality for Random Fuzzy Mappings Hongxia Dai

Unit 10. The Lie Algebra of Vector Fields

National Conference on Recent Trends in Synthesis and Characterization of Futuristic Material in Science for the Development of Society

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 9, Number 3/2008, pp

Bianchi Type II Stiff Fluid Tilted Cosmological Model in General Relativity

A note on Turán number Tk ( 1, kn, )

The Poisson Process Properties of the Poisson Process

Learning of Graphical Models Parameter Estimation and Structure Learning

1. Consider an economy of identical individuals with preferences given by the utility function

Solving fuzzy linear programming problems with piecewise linear membership functions by the determination of a crisp maximizing decision

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations

Geometric Modeling

A Remark on Polynomial Mappings from to

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction

Representation of Hamiltonian Formalism. in Dissipative Mechanical System

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state)

Cyclically Interval Total Colorings of Cycles and Middle Graphs of Cycles

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA

Midterm Exam. Tuesday, September hour, 15 minutes

A Comparison of AdomiansDecomposition Method and Picard Iterations Method in Solving Nonlinear Differential Equations

Moments of Order Statistics from Nonidentically Distributed Three Parameters Beta typei and Erlang Truncated Exponential Variables

Other Topics in Kernel Method Statistical Inference with Reproducing Kernel Hilbert Space

Asymptotic Regional Boundary Observer in Distributed Parameter Systems via Sensors Structures

Density estimation III.

Integral Φ0-Stability of Impulsive Differential Equations

Partial Molar Properties of solutions

Domination in Controlled and Observed Distributed Parameter Systems

( 1)u + r2i. f (x2i+1 ) +

Complementary Tree Paired Domination in Graphs

The MacWilliams Identity of the Linear Codes over the Ring F p +uf p +vf p +uvf p

A Second Kind Chebyshev Polynomial Approach for the Wave Equation Subject to an Integral Conservation Condition

Fundamentals of Speech Recognition Suggested Project The Hidden Markov Model

Optimal Control and Hamiltonian System

Continuous Random Variables: Conditioning, Expectation and Independence

A New Generalized Gronwall-Bellman Type Inequality

Factorization of Finite Abelian Groups

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS

Cyclone. Anti-cyclone

. The set of these sums. be a partition of [ ab, ]. Consider the sum f( x) f( x 1)

Binary Time-Frame Expansion

A Recurrent Neural Network to Identify Efficient Decision Making Units in Data Envelopment Analysis

A New Iterative Method for Solving Initial Value Problems

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters

(1) Cov(, ) E[( E( ))( E( ))]

March 14, Title: Change of Measures for Frequency and Severity. Farrokh Guiahi, Ph.D., FCAS, ASA

Density estimation III.

Solution to Some Open Problems on E-super Vertex Magic Total Labeling of Graphs

Chapter 1 - Free Vibration of Multi-Degree-of-Freedom Systems - I

Solution set Stat 471/Spring 06. Homework 2

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur

Fourth Order Runge-Kutta Method Based On Geometric Mean for Hybrid Fuzzy Initial Value Problems

THE POLYNOMIAL TENSOR INTERPOLATION

General Complex Fuzzy Transformation Semigroups in Automata

On g Evaluations with L p Domains under Jump Filtration

Linear Regression Linear Regression with Shrinkage

PHYS 1443 Section 001 Lecture #4

K3 p K2 p Kp 0 p 2 p 3 p

LECTURE 8: Topics in Chaos Ricker Equation. Period doubling bifurcation. Period doubling cascade. A Quadratic Equation Ricker Equation 1.0. x x 4 0.

NUMERICAL EVALUATION of DYNAMIC RESPONSE

( ) ( ) ( ( )) ( ) ( ) ( ) ( ) ( ) = ( ) ( ) + ( ) ( ) = ( ( )) ( ) + ( ( )) ( ) Review. Second Derivatives for f : y R. Let A be an m n matrix.

As evident from the full-sample-model, we continue to assume that individual errors are identically and

Numerical Methods for a Class of Hybrid. Weakly Singular Integro-Differential Equations.

IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC

Some probability inequalities for multivariate gamma and normal distributions. Abstract

4 5 = So 2. No, as = ± and invariant factor 6. Solution 3 Each of (1, 0),(1, 2),(0, 2) has order 2 and generates a C

The Mean Residual Lifetime of (n k + 1)-out-of-n Systems in Discrete Setting

Probability Bracket Notation and Probability Modeling. Xing M. Wang Sherman Visual Lab, Sunnyvale, CA 94087, USA. Abstract

Optimal control for multi-input bilinear systems with an application in cancer chemotherapy.

P-Convexity Property in Musielak-Orlicz Function Space of Bohner Type

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits.

Bilinear estimation of pollution source profiles in receptor models. Clifford H Spiegelman Ronald C. Henry NRCSE

Real-time Classification of Large Data Sets using Binary Knapsack

Transcription:

THE PUBLIHING HOUE PROCEEDING OF THE ROMANIAN ACADEMY, eres A, OF THE ROMANIAN ACADEMY Volume 0, Number /009,. 000-000 ON ZALMAI EMIPARAMETRIC DUALITY MODEL FOR MULTIOBJECTIVE FRACTIONAL PROGRAMMING WITH -ET FUNCTION Ioa M. TANCU-MINAIAN, Vasle PREDA, Mrua BELDIMAN, Adreea Mădăla TANCU Isue o Mahemacal ascs ad Aled Mahemacs o he Romaa Academy, Calea 3 eembre r. 3, 0507, Buchares 5, Romaa, E-mal: sacum@csm.ro Uversy o Buchares, Faculy o Mahemacs ad Comuer ceces, r. Academe 4, 0004, Buchares, Romaa New dualy resuls or a semaramerc dualy model are gve or a racoal rogrammg roblem volvg -se ucos. Key words: mulobecve rogrammg, -se uco, dualy, geeralzed covexy.. INTRODUCTION AND PRELIMINARIE We cosder he rame o omzao heory or -se [,5,8]. For ormulag ad rovg varous dualy resuls, we use he class o geeralzed covex -se ucos called (F,b,φ,ρ, θ)-uvex ucos, whch were deed Zalma []. Ul ow, F was assumed o be a sublear uco he hrd argume. I our aroach, we suose ha F s a covex uco he hrd argume, as Preda e al. [7,8] ad Băăorescu e al. []. Le ( X, A, μ ) be a e aomless measure sace wh L ( X, A, μ ) searable, ad le d be he seudomerc o A deed by d( R, ) : = μ ( RΔ) = where R = ( R,, R ), = (,, ) Aⁿ ad Δ sads or symmerc derece. Thus, ( Aⁿ, d) s a seudomerc sace. For h L ( X, A, μ ) ad T A wh dcaor (characersc) uco χt L ( X, A, μ ), he egral hdμ s deoed by h, χ T. Deo.. [4] A uco : A s sad o be dereable a A here exs D ( ) L ( X, A,μ ), called he dervave o a, ad V : A A such ha ( ) = F( ) D ( ), χ χ V (, ) or each A, where V (, ) s od ( (, )), ha s, 0 d(, ) 0 V (, ) lm = 0. d (, ) /

Ioa M. TANCU-MINAIAN, Vasle PREDA, Mrua BELDIMAN, Adreea Mădăla TANCU Deo.. [] A uco g : A s sad o have a aral dervave a =(,..., ) Aⁿ wh resec o s -h argume he uco ( ) = g (,,,,,, ) has dervave D( ), = {,,..., }. We dee D g ( ) = D ( ) ad wre D g ( ) = (D g ( ),,D g ( )). Deo.3. [] A uco g: Aⁿ R s sad o be dereable a here exs Dg( ) ad W g : Aⁿ Aⁿ R such ha χ χ G = G ( ) = G ( ) D G ( ), W(, ), where (, ) WG s od ( (, )) or all Aⁿ. Le be he -dmesoal Eucldea sace ad ( ) s osve orha,.e. = { x = x,, x : x 0, =,, }. For ay vecors x ( x,, x ) ad y ( y,, y ) = =, we u x y x y, or each ={,,...,}; x y x y, wh x y; x < y x < y, or each = {,,...}; x y meas he egao o x y. Clearly, x x 0. I hs aer, we cosder he mulobecve racoal subse rogrammg roblem subec o ( ) ( ) ( ) Φ = g ( ) g ( ) g ( ) (P) m ( ),,, { } h ( ) 0, =,,,, A, where Aⁿ s he -old roduc o he σ-algebra A o subses o a gve se X, : Aⁿ, g : Aⁿ, { } =,,...,, ad h : A, deoed by ⁿ, such ha ( ) 0 ( ) P = { Aⁿ : h 0, } he se o all easble soluos o (P). Deo.4. A easble soluo oher easble soluo P such ha g > or each ad all P. We 0 P s sad o be a ece soluo o (P) here exss o g g g g g g 0 0 0 ( ) ( ) ( ) ( ) ( ) ( ),,,,,, 0 0 0 ( ) ( ) ( ) ( ) ( ) ( ) I he ollowg we cosder F: Aⁿ Aⁿ R R ad a dereable uco : Aⁿ. The deos below uy he coces o ( F, ρ ) covexy, ( F, ρ ) seudocovexy, ( F, ρ ) uascovexy rom Preda [6] ad uvexy, seudouvexy, uasuvexy rom Mshra [3]. Le b : Aⁿ Aⁿ, θ : Aⁿ Aⁿ Aⁿ Aⁿ such ha θ(, ) (0,0), φ : R R, ad a real umber ρ. Deo.5. [] A uco s sad o be (srcly) ( Fbϕρθ,,,, ) uvex a or each A. ( ) ( > ) ( ) ρ ( θ ( )) ϕ( F F( )) F(, ; b, D F( )) d²,

3 Mulobecve rogrammg roblems wh geeralzed V-ye uvexy Deo.6. [] A uco s sad o be (srcly) (F,b,φ,ρ,θ)-seudouvex a ( ) ρ ( θ( )) ϕ ( ) ( > ) F b d (, ;, D ( )) ², ( ( )) 0 or each A,. Deo.7. [] A uco s sad o be (resrcly) (F,b,φ,ρ,θ)-uasuvex a ( ) ( < ) ( ) ρ ( θ ( )) ϕ( ( )) 0 F(, ; b, D ( )) d², or each A. For roblem (P), Zalma [0] gave he ecessary codos or ececy below. Theorem.. Assume ha, g,, ad h,, are dereable a A, ad ha or each here exss ˆ A, such ha ad or each l \ { } we have ( ) D h( ), χ ˆ χ = < 0, h, = g g χ χ ( )D l( ) ( )D l( ), ˆ < 0. I s a ece soluo o (P), he here exss u U = { u : u > 0, u = } ad such ha u g g v h χ χ = = = [ ( )D ( ) ( )D ( )] D ( ), 0 = v >, () or all Aⁿ, vh( ) = 0,. We shall reer o a ece soluo some,, as a ormal ece soluo. ˆ o (P) sasyg he rs wo codos Theorem. or.the DUALITY MODEL AND DUALITY REULT I hs seco we rese a geeral dualy model or (P). Here we use wo aros o he dex ses ad, resecvely. J, J,..., J m a aro o he dex se such I, I,..., I be a aro o he dex se ad { } Le { } 0 ha K={0,,...,} M={0,,...,m}, ad, or xed, u ad v, ad K le he uco Ω ( ;, u, v): Aⁿ be deed by 0 ( Tuv,,, ) u[ ( ) g ( T ) ( T ) g ( ) ] v h ( T ) Ω = I We assocae wh roblem (P) he dual roblem

Ioa M. TANCU-MINAIAN, Vasle PREDA, Mrua BELDIMAN, Adreea Mădăla TANCU 4 subec o ( T) ( T) ( T ) max δ,, =,,, g ( T ) g ( T ) g ( T ) ( D ) ( Tuv) F, T; b(, T) u [ G ( T) DF ( T) F ( T) DG ( T) ] v Dh ( T) x 0 A ⁿ = = J ( ) vh T 0, M T A, u U, v I he ollowg we cosder a covex uco F(, T; ) : L ( X, A, μ) Λ v A (, ):, Λ = ( T, v ) J vh( T), M.. ad The resul below esablshes several versos o wea dualy relaed o roblems (P) ad (D). Theorem. (Wea dualy). Le ad (T,u,v) be arbrary easble soluos o (P) ad (D), resecvely, ad assume ha ay oe o he ollowg ses o hyoheses s sased: (a) () Ω (, T, u, v s srcly ) seudouvex a T, ϕ s creasg, ad ϕ ( 0) = 0 or each K ; () ( ) Λ (, v s ) uasuvex a T, ϕ s creasg, ad ϕ ( 0) = 0 or each M\K; ρ () ρ K M\K (b) () Ω (, T, u, v s resrcly ) uasuvex a T, ϕ s creasg, ad ϕ ( 0) = 0 or each K ; () ( ) Λ (, v) s srcly ( Fbϕ,,, ρ, θ ) seudouvex a T, ϕ s crea sg, ad ϕ ( 0) = 0 or each M\K; ρ () ρ K M\K (c) () Ω (, T, u, v s resrcly ) ( Fbϕ,,, ρ, θ ) uasuvex a T, ϕ s creasg, ad ϕ ( 0) = 0 or each K ; () ( ) Λ (, v s ) uasuvex a T, ϕ s creasg, ad ϕ ( 0) = 0 or each M\K; ρ () ρ K M\K (d) () 3 Ω (, T, u, v s srcly ) seudouvex a T or each K, ϕ s creasg, ad ϕ ( 0) = 0 or each K, 3 Ω (, T, u, v ) s resrcly ( Fbϕ,,, ρ, θ ) uasuvex a T or each K, ϕ s creasg, ad ϕ ( 0) = 0 or each K, where { } s a aro o K, wh K,K K, K,, ; = K = K () 3 ( ) Λ (, v s ) uasuvex a T, ϕ s creasg, ad ϕ ( 0) = 0 or each M\K;

5 Mulobecve rogrammg roblems wh geeralzed V-ye uvexy ρ () ρ ρ K K M\K (e) () 3 Ω (, T, u, v) s resrcly ( F, b, ϕ, ρ, θ ) uasuvex a T, ϕ s creasg, ad ϕ ( 0) = 0 or each K ; () 3( m ) Λ (, v ) s srcly ( Fb,, ϕ, ρ, θ ) seudouvex a T or each (M \ K), ϕ s creasg, ad ϕ ( 0) = 0 or each (M \ K), 3 ( m ) Λ (, v ) s ( F, b, ϕ, ρ, θ ) uasuvex a T or each (M \ K), ϕ s creasg, ad ϕ ( 0) = 0 or each (M \ K), where {( M\K ),( M \K) } s a aro o M\K, wh ( M\K), m = ( M\K ), ( M\ K ), = ( M\ ) () ρ ρ m m ρ K (M\K) (M\K) 4 (, ) ( F,,,, ) 4 Ω (, T, u, v ) s resrcly (,,,, ) () () Ω T, u, v s srcly or each ( ) K, K ; m bϕ ρ θ seudouvex a T, ϕ s s ϕ 0 = 0 Fbϕ ρ θ uasuvex a T, ϕ s creasg ad, crea g, ad ( ) ϕ 0 = 0 or each K, where { K,K } s a aro o K, wh K, K, = K, = K ; () 4( m ) Λ (, v ) s srcly ( Fb,, ϕ, ρ, θ ) ϕ ( 0) = 0 or each (M \ K ), 4 ( m ) Λ (, v) s ( Fb,,,, ) creasg, ad ϕ ( 0) = 0 or each (M \ K), where { ( ) ( ) ( M\K ), m = ( M\K), ( M\ K ), m = ( M\ K ) ; ρ ρ () ρ ρ m m K K (M\K) (M\K) (v) K or or ( M\K) ρ ρ ρ ρ > K K (M\K) m (M\K) m The Φ / δ T, u, v. ( ) ( ) Theorem.. (rog dualy). Le D ( ), = seudouvex a T, ϕ s cre asg, ad ϕ ρ θ ϕ s M\ K, M\K } s a aro o M\K, wh P be a ormal ece soluo o (P), le F (, ;D ( )) = χ χ or ay dereable uco : Aⁿ ad Aⁿ, ad assume ha ay oe o he ses o hyoheses seced Theorem.. holds or all easble soluos o (D). The here exs u U ad v such ha (, u, v ) s a ece soluo o (D) ad Φ ( ) = δ (, u, v ). Remar.. Usg Theorems. ad., ad ehues rom [5] ad [0], we ca also oba a src coverse dualy resul. For a dealed reseao o hese resuls, he reader s reerred o [9]. 3. CONCLUION We have obaed dualy resuls or a dual model o Zalma [0], relacg he assumo o subleary by ha o covexy. mlar resuls ca be obaed or he oher dual models rom [0]. Also, almos all resuls o hs ye rese he leraure ca be exeded o he case where F s o ecessarly sublear.

Ioa M. TANCU-MINAIAN, Vasle PREDA, Mrua BELDIMAN, Adreea Mădăla TANCU 6 ACKNOWLEDGEMENT Ths wor was arally suored by Gra PN II IDEI o. /007. REFERENCE. BĂTĂTORECU, A., PREDA, V., BELDIMAN, M., O hgher order dualy or mulobecve rogrammg volvg geeralzed (F,ρ,γ,b)-covexy, Mah. Re. (Bucur.) 9(59) (007), 6-74.. CORLEY, H. W., Omzao heory or -se ucos, J. Mah. Aal. Al. 7 (987), 93-05. 3. MIHRA,.K., Dualy or mulle obecve racoal subse rogrammg wh geeralzed (F,ρ,σ,θ)-V-ye-I ucos, J. Global Om. 36 (006)4, 499-56. 4. MORRI, R. J. T., Omal cosraed seleco o a measurable subse, J. Mah. Aal. Al. 70(979), 546-56. 5. PREDA, V., O mmax rogrammg roblems coag -se ucos, Omzao (99)4, 57-537. 6. PREDA, V., O ececy ad dualy or mulobecve rogramms, J. Mah. Aal. Al. 66 (99), 365-377. 7. PREDA, V., TANCU-MINAIAN, I.M., BELDIMAN, M., TANCU, A., Omaly ad dualy or mulobecve rogrammg wh geeralzed V-ye I uvexy ad relaed -se ucos, Proc. Rom. Acad. er. A Mah. Phys. Tech. c. I. c. 6(005)3, 83-9. 8. PREDA, V., TANCU-MINAIAN, I.M., BELDIMAN, M., TANCU, A., Geeralzed V-uvexy ye-i or mulobecve rogrammg roblems wh - se uco, o aear J. Global Om., 009. 9. PREDA, V., TANCU-MINAIAN, I.M., BELDIMAN, M., TANCU, A., Dualy or mulobecve racoal rogrammg wh geeralzed (F,b,φ,ρ,θ)-uvex -se ucos, submed. 0. ZALMAI, G. J., Ececy codos ad dualy models or mulobecve racoal subse rogrammg roblems wh geeralzed (F,α,ρ,θ)-V-covex ucos, Com. Mah. Al. 43 (00), 489-50.. ZALMAI, G. J., Geeralzed (F,b,φ,ρ,θ)-uvex -se ucos ad global semaramerc suce ececy codos mulobecve racoal subse rogrammg, I. J. Mah. Mah. c. 6(005), 949-973. Receved February 3, 009