A Monotonic Optimization Approach for Solving Strictly Quasiconvex Multiobjective Programming Problems

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS(2020)

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Abstract
In this article, we use a monotonic optimization approach to propose an outcome-space outer approximation by copolyblocks for solving strictly quasiconvex multiobjective programming problems which include many classes of captivating problems, for example when the criterion functions are nonlinear fractional. After the algorithm is terminated, with any given tolerance, an approximation of the weakly efficient solution set is obtained containing the whole weakly efficient solution set of the problem. The algorithm is proved to be convergent and it is suitable to be implemented in parallel using convex programming tools. Some computational experiments are reported to show the accuracy and efficiency of the algorithm.
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Key words
Multiobjective programming,monotonic optimization,strictly quasiconvex,outcome space,outer approximation
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