A Hybrid Gray Wolf Weed Algorithm for Flexible Job-shop Scheduling Problem

Autor:	Lei Qi, Xin-kun Wang, Yi Wang, Yu-ji Zou, Yu-chuan Song
Rok vydání:	2021
Předmět:	History Mathematical optimization ved/biology Computer science ved/biology.organism_classification_rank.species Job shop scheduling problem Gray wolf Weed Computer Science Applications Education
Zdroj:	Journal of Physics: Conference Series. 1828:012162
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1828/1/012162
Popis:	For the flexible job shop scheduling problem with the goal of makespan, a mathematical model is established and a hybrid algorithm (GIWO) based on gray wolf and invasive weeds is proposed. In this paper, the intrusive weed optimization algorithm is embedded on the basis of the gray wolf algorithm to improve the algorithm’s global search and local search ability. And an effective initial population generation mechanism is added to improve the quality of the initial solution. A variable neighborhood search structure that adaptively changes according to the search is proposed. Finally, other improved gray wolf algorithms are compared with the algorithm in this paper through different benchmark instances. Experimental results show that the proposed algorithm performs better than the other algorithms in effectiveness and superiority. The algorithm can effectively solve the flexible job shop scheduling problem.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::595dbe13ba4b0fbf9261ef956841b5ab https://doi.org/10.1088/1742-6596/1828/1/012162 Zobrazit plný text záznamu