Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Enhancing Decomposition Approach for Solving Multi-Objective Dynamic Non-Linear Programming Problems Involving Fuzziness

Version 1 : Received: 8 June 2023 / Approved: 9 June 2023 / Online: 9 June 2023 (11:28:09 CEST)

A peer-reviewed article of this Preprint also exists.

Kumar, P.; Khalifa, H.A.-W. Enhancing Decomposition Approach for Solving Multi-Objective Dynamic Non-Linear Programming Problems Involving Fuzziness. Mathematics 2023, 11, 3123. Kumar, P.; Khalifa, H.A.-W. Enhancing Decomposition Approach for Solving Multi-Objective Dynamic Non-Linear Programming Problems Involving Fuzziness. Mathematics 2023, 11, 3123.

Abstract

In real-life scenario, there are many mathematical tools to handle the incomplete and imprecise data. One of them is the fuzzy approach. This article aims to contribute to the literature of fuzzy multi-objective dynamic programming issues involving the fuzzy objective functions. The piecewise quadratic fuzzy numbers characterize these fuzzy parameters. Some basic notions in the problem under the α-pareto optimal solution concept is redefined and analyzed to study the stability of the problem. Furthermore, a technique, named as enhancing decomposition approach, is presented for achieving a subset for the parametric space that contains the sameα-pareto optimal solution. For a better understanding and comprehension of the suggested concept, a numerical example is provided.

Keywords

Optimization problem Multi-objective optimization problems; Dynamic non-linear programming; Fuzzy set; Piecewise quadratic fuzzy numbers; Close interval approximation; α-pareto optimal solution; Decision- making; Stability

Subject

Computer Science and Mathematics, Mathematics

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