A Comprehensive Survey of Metaheuristic Algorithms Applying in Mechanical Design Optimization Problems

EasyChair Preprint no. 9201

Abstract

Metaheuristic algorithms have received great popularity since the first metaheuristic algorithm—Genetic Algorithm—was proposed in 1975. However, conventionally the performances of metaheuristic algorithms are evaluated by a series of unconstrained mathematical functions. Unfortunately, in real-world problems, for example, mechanical design optimization problems, the landscapes of the search area are far different from mathematical ones, and most importantly, the constraints are almost always imposed. Therefore, in this work, 19 metaheuristic algorithms have been implemented to solve three mechanical design optimization problems and evaluate their performance. Results show that the performances of metaheuristic algorithms could be determined by the initial convergence speed.

Keyphrases: evolutionary algorithm, mechanical design, metaheuristic algorithm, Optimization

@Booklet{EasyChair:9201,
  author = {Hsu-Hsing Chen and Feng-Cheng Yang},
  title = {A Comprehensive Survey of Metaheuristic Algorithms Applying in Mechanical Design Optimization Problems},
  howpublished = {EasyChair Preprint no. 9201},

  year = {EasyChair, 2022}}