A Hybrid Search Model for Constrained Optimization

Autor: Xiaoli Gao, Yangfei Yuan, Jie Li, Weifeng Gao
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Discrete Dynamics in Nature and Society, Vol 2022 (2022)
Druh dokumentu: article
ISSN: 1607-887X
DOI: 10.1155/2022/1190174
Popis: This paper proposes a hybrid model based on decomposition for constrained optimization problems. Firstly, a constrained optimization problem is transformed into a biobjective optimization problem. Then, the biobjective optimization problem is divided into a set of subproblems, and different subproblems are assigned to different Fitness functions by the direction vectors. Different from decomposition-based multiobjective optimization algorithms in which each subproblem is optimized by using the information of its neighboring subproblems, the neighbors of each subproblem are deFined based on corresponding direction vector only in the method. By combining three main components, namely, the local search model, the global search model, and the direction vector adjusting strategy, the population can gradually move toward the global optimal solution. Experiments on two sets of test problems and Five real-world engineering design problems have shown that the proposed method performs better than or is competitive with other compared methods.
Databáze: Directory of Open Access Journals
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