Improved Chef-Based Optimization Algorithm with Chaos-Based Fitness Distance Balance for Frequency-Constrained Truss Structures

Abstract

Chef-based optimization algorithm (CBOA), one of the recently proposed metaheuristic algorithms, is a population-based optimization algorithm inspired by the process of students becoming skilled chefs after receiving training from chef instructors in a culinary academy. In order to improve the performance of CBOA, seven different CBOA variants are proposed in this study, which are improved with three different chaotic maps, fitness distance balance strategy and their combinations. The effectiveness of the proposed CBOA variants is first evaluated by testing them on 16 different benchmark functions. Then, the proposed CBOA variants are applied to frequency constrained 37-bar and 52-bar truss problems to evaluate their performance on engineering problems. Thus, the success of the proposed CBOA variants on different problems was extensively investigated in three different experimental studies. Among these variants, while FC2-CBOA and FC3-CBOA variants performed well on benchmark functions, FC3-CBOA and C3-CBOA variants performed well on 37-bar and 52-bar truss problems, respectively. The results obtained from these three different experimental studies have shown that each proposed CBOA variant is able to produce effective results depending on the problem type.

Keywords

• Chaotic Maps
• Fitness Distance Balance
• Truss Structure
• Chef-based Optimization Algorithm

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