Modified whale optimization algorithm for solving unrelated parallel machine scheduling problems; Soft Computing; Vol. 25, iss. 17

Modified whale optimization algorithm for solving unrelated parallel machine scheduling problems; Soft Computing; Vol. 25, iss. 17

Bibliografiska uppgifter
Parent link:	Soft Computing Vol. 25, iss. 17.— 2021.— [153, 13 p.]
Huvudupphovsman:	Al-qaness Mohammed A. A.
Institutionell upphovsman:	Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники
Övriga upphovsmän:	Ewees Ahmed A., Mokhamed Elsaed A. M. Akhmed Mokhamed
Sammanfattning:	Title screen Unrelated parallel machine scheduling problem (UPMSP) with sequence-dependent setup times is considered a hot topic among the researchers, as it presents more complexity to be able to find an optimal solution. Many efforts have been made to solve UPMSP problems and established their performances. Therefore, in this study, a new method is introduced to address UPMSP problems with sequence-dependent and machine-dependent setup time. Our proposed method utilizes two meta-heuristic techniques, the whale optimization algorithm (WOA) and the firefly algorithm (FA), by combining their features to perform this task. The hybrid model is called WOAFA. For more detail, the operators of the FA are employed to improve the exploitation ability of the WOA by serving as a local search. Moreover, the quality of the proposed WOAFA method is tested by comparing with well-known meta-heuristic algorithms over six machines and six jobs, namely (2, 4, 6, 8, 10, and 12 machines) and (20, 40, 60, 80, 100, and 120 jobs).
Språk:	engelska
Publicerad:	2021
Ämnen:	электронный ресурс труды учёных ТПУ whale optimization algorithm firefly algorithm meta-heuristic unrelated parallel machine scheduling problem local search
Länkar:	https://doi.org/10.1007/s00500-021-05889-w
Materialtyp:	Elektronisk Bokavsnitt
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=665108

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