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

Bibliographic Details
Parent link:Soft Computing
Vol. 25, iss. 17.— 2021.— [153, 13 p.]
Main Author: Al-qaness Mohammed A. A.
Corporate Author: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Отделение информационных технологий
Other Authors: Ewees Ahmed A., Mokhamed Elsaed A. M. Akhmed Mokhamed
Summary: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).
Language:English
Published: 2021
Subjects:
Online Access:https://doi.org/10.1007/s00500-021-05889-w
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=665108

MARC

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330 |a 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). 
461 |t Soft Computing 
463 |t Vol. 25, iss. 17  |v [153, 13 p.]  |d 2021 
610 1 |a электронный ресурс 
610 1 |a труды учёных ТПУ 
610 1 |a whale optimization algorithm 
610 1 |a firefly algorithm 
610 1 |a meta-heuristic 
610 1 |a unrelated parallel machine scheduling problem 
610 1 |a local search 
700 1 |a Al-qaness Mohammed  |b A. A. 
701 1 |a Ewees Ahmed  |b A. 
701 1 |a Mokhamed Elsaed  |b A. M.  |c Specialist in the field of informatics and computer technology  |c Professor of Tomsk Polytechnic University  |f 1987-  |g Akhmed Mokhamed  |3 (RuTPU)RU\TPU\pers\46943 
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