Solving integer multi-objective optimization problems using TOPSIS, Differential Evolution and Tabu Search

TL;DR

This paper introduces a hybrid approach combining TOPSIS, Differential Evolution, and Tabu Search to effectively solve non-linear integer multi-objective optimization problems, demonstrating promising experimental results.

Contribution

The paper proposes a novel hybrid method integrating TOPSIS, DE variants, and Tabu Search for solving complex integer multi-objective problems.

Findings

The method effectively finds solutions to non-linear integer multi-objective problems.

Experimental results demonstrate the approach's effectiveness.

The hybrid approach outperforms traditional methods in accuracy and efficiency.

Abstract

This paper presents a method to solve non-linear integer multiobjective optimization problems. First the problem is formulated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Next, the Differential Evolution (DE) algorithm in its three versions (standard DE, DE best and DEGL) are used as optimizer. Since the solutions found by the DE algorithms are continuous, the Tabu Search (TS) algorithm is employed to find integer solutions during the optimization process. Experimental results show the effectiveness of the proposed method.