Metaheuristic Algorithms in Optimal Design of Engineering Problems
Ngày
2025
Tác giả
Knypiński, Łukasz
Devarapalli, Ramesh
Kaminski, Marcin
Tên Tạp chí
Tạp chí ISSN
Nhan đề tập
Nhà xuất bản
MDPI
Giấy phép
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Tóm tắt
Metaheuristic algorithms are advanced optimization methods widely used to solve complex engineering design problems. They operate by iteratively searching the solution space, employing strategies inspired by natural or physical processes to balance exploration and exploitation. Common examples include genetic algorithms, particle swarm optimization, simulated annealing, and ant colony optimization. These algorithms are effective for large-scale, nonlinear, and non-convex problems, making them valuable in fields such as mechanical, civil, electrical, and aerospace engineering. Metaheuristics can efficiently find near-optimal solutions where traditional methods may fail or become computationally expensive. Their performance depends on factors like initial solution quality, algorithm selection, and parameter tuning. By integrating metaheuristics with domain-specific knowledge, engineers can optimize system designs to meet performance, cost, and operational constraints. As research progresses, metaheuristic algorithms continue to expand their applicability and effectiveness in solving real-world engineering challenges.
Mô tả
238 p.
Từ khóa
Optimization , multi-objective optimization , engineering problems , particle swarm optimization , metaheuristic optimization algorithms