• Title/Summary/Keyword: vector optimization problem

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ON SECOND ORDER NECESSARY OPTIMALITY CONDITIONS FOR VECTOR OPTIMIZATION PROBLEMS

  • Lee, Gue-Myung;Kim, Moon-Hee
    • Journal of the Korean Mathematical Society
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    • v.40 no.2
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    • pp.287-305
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    • 2003
  • Second order necessary optimality condition for properly efficient solutions of a twice differentiable vector optimization problem is given. We obtain a nonsmooth version of the second order necessary optimality condition for properly efficient solutions of a nondifferentiable vector optimization problem. Furthermore, we prove a second order necessary optimality condition for weakly efficient solutions of a nondifferentiable vector optimization problem.

ON LINEARIZED VECTOR OPTIMIZATION PROBLEMS WITH PROPER EFFICIENCY

  • Kim, Moon-Hee
    • Journal of applied mathematics & informatics
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    • v.27 no.3_4
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    • pp.685-692
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    • 2009
  • We consider the linearized (approximated) problem for differentiable vector optimization problem, and then we establish equivalence results between a differentiable vector optimization problem and its associated linearized problem under the proper efficiency.

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ON OPTIMALITY THEOREMS FOR SEMIDEFINITE LINEAR VECTOR OPTIMIZATION PROBLEMS

  • Kim, Moon Hee
    • East Asian mathematical journal
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    • v.37 no.5
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    • pp.543-551
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    • 2021
  • Recently, semidefinite optimization problems have been intensively studied since many optimization problem can be changed into the problems and the the problems are very computationable. In this paper, we consider a semidefinite linear vector optimization problem (VP) and we establish the optimality theorems for (VP), which holds without any constraint qualification.

GENERALIZATIONS OF ISERMANN'S RESULTS IN VECTOR OPTIMIZATION

  • Lee, Gue-Myung
    • Bulletin of the Korean Mathematical Society
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    • v.30 no.1
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    • pp.1-7
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    • 1993
  • Vector optimization problems consist of two or more objective functions and constraints. Optimization entails obtaining efficient solutions. Geoffrion [3] introduced the definition of the properly efficient solution in order to eliminate efficient solutions causing unbounded trade-offs between objective functions. In 1974, Isermann [7] obtained a necessary and sufficient condition for an efficient solution of a linear vector optimization problem with linear constraints and showed that every efficient solution is a properly efficient solution. Since then, many authors [1, 2, 4, 5, 6] have extended the Isermann's results. In particular, Gulati and Islam [4] derived a necessary and sufficient condition for an efficient solution of a linear vector optimization problem with nonlinear constraints, under certain assumptions. In this paper, we consider the following nonlinear vector optimization problem (NVOP): (Fig.) where for each i, f$_{i}$ is a differentiable function from R$^{n}$ into R and g is a differentiable function from R$^{n}$ into R$^{m}$ .

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OPTIMALITY AND DUALITY IN NONSMOOTH VECTOR OPTIMIZATION INVOLVING GENERALIZED INVEX FUNCTIONS

  • Kim, Moon-Hee
    • Journal of applied mathematics & informatics
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    • v.28 no.5_6
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    • pp.1527-1534
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    • 2010
  • In this paper, we consider nonsmooth optimization problem of which objective and constraint functions are locally Lipschitz. We establish sufficient optimality conditions and duality results for nonsmooth vector optimization problem given under nearly strict invexity and near invexity-infineness assumptions.

ON OPTIMALITY CONDITIONS FOR ABSTRACT CONVEX VECTOR OPTIMIZATION PROBLEMS

  • Lee, Gue-Myung;Lee, Kwang-Baik
    • Journal of the Korean Mathematical Society
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    • v.44 no.4
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    • pp.971-985
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    • 2007
  • A sequential optimality condition characterizing the efficient solution without any constraint qualification for an abstract convex vector optimization problem is given in sequential forms using subdifferentials and ${\epsilon}$-subdifferentials. Another sequential condition involving only the subdifferentials, but at nearby points to the efficient solution for constraints, is also derived. Moreover, we present a proposition with a sufficient condition for an efficient solution to be properly efficient, which are a generalization of the well-known Isermann result for a linear vector optimization problem. An example is given to illustrate the significance of our main results. Also, we give an example showing that the proper efficiency may not imply certain closeness assumption.

INTERVAL VALUED VECTOR VARIATIONAL INEQUALITIES AND VECTOR OPTIMIZATION PROBLEMS VIA CONVEXIFICATORS

  • TIRTH RAM;ROHIT KUMAR BHARDWAJ
    • Journal of applied mathematics & informatics
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    • v.41 no.6
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    • pp.1419-1432
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    • 2023
  • In this study, we take into account interval-valued vector optimization problems (IVOP) and obtain their relationships to interval vector variational inequalities (IVVI) of Stampacchia and Minty kind in aspects of convexificators, as well as the (IVOP) LU-efficient solution under the LU-convexity assumption. Additionally, we examine the weak version of the (IVVI) of the Stampacchia and Minty kind and determine the relationships between them and the weakly LU-efficient solution of the (IVOP). The results of this study improve and generalizes certain earlier results from the literature.

Reliability-Based Topology Optimization Using Single-Loop Single-Vector Approach (단일루프 단일벡터 방법을 이용한 신뢰성기반 위상최적설계)

  • Bang Seung-Hyun;Min Seung-Jae
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.30 no.8 s.251
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    • pp.889-896
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    • 2006
  • The concept of reliability has been applied to the topology optimization based on a reliability index approach or a performance measure approach. Since these approaches, called double-loop single vector approach, require the nested optimization problem to obtain the most probable point in the probabilistic design domain, the time for the entire process makes the practical use infeasible. In this work, new reliability-based topology optimization method is proposed by utilizing single-loop single-vector approach, which approximates searching the most probable point analytically, to reduce the time cost. The results of design examples show that the proposed method provides efficiency curtailing the time for the optimization process and accuracy satisfying the specified reliability.