Modified Harris Hawks Optimizer for Solving Machine Scheduling Problems

Symmetry

Robertas Damaševičius¹  Marcin Korytkowski²  MohamedAbd Elaziz³  AhmedA. Ewees⁴  Deming Lei⁵  Hamza Jouhari⁵  MohammedA. A. Al-qaness⁶ 

[1] Department of Applied Informatics, Vytautas Magnus University, 44404 Kaunas, Lithuania;Department of Intelligent Computer Systems, Czestochowa University of Technology, 42-200 Częstochowa, Poland;Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt;Department of e-Systems, University of Bisha, Bisha 61922, Saudi Arabia;School of Automation, Wuhan University of Technology, Wuhan 430070, China;State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;

关键词: scheduling;    symmetry;    unrelated parallel machine scheduling problems;    harris hawks optimizer;    salp swarm algorithm;   

DOI  :  10.3390/sym12091460

来源: DOAJ

【 摘 要 】

Scheduling can be described as a decision-making process. It is applied in various applications, such as manufacturing, airports, and information processing systems. More so, the presence of symmetry is common in certain types of scheduling problems. There are three types of parallel machine scheduling problems (PMSP): uniform, identical, and unrelated parallel machine scheduling problems (UPMSPs). Recently, UPMSPs with setup time had attracted more attention due to its applications in different industries and services. In this study, we present an efficient method to address the UPMSPs while using a modified harris hawks optimizer (HHO). The new method, called MHHO, uses the salp swarm algorithm (SSA) as a local search for HHO in order to enhance its performance and to decrease its computation time. To test the performance of MHHO, several experiments are implemented using small and large problem instances. Moreover, the proposed method is compared to several state-of-art approaches used for UPMSPs. The MHHO shows better performance in both small and large problem cases.

【 授权许可】

Unknown