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NSGA-II variants for solving a social-conscious dual resource-constrained scheduling problem
Akbar M.b, Irohara T.
a Green Science and Engineering Division, Faculty of Science and Technology, Sophia University, Tokyo, 102-8554, Japan
b Department of Industrial Engineering, Bandung Institute of Technology, Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020 Elsevier LtdThis present study compares various non-dominated sorting genetic algorithm II (NSGA-II) variants to deal with multi-task simultaneous supervision dual resource-constrained (MTSSDRC) scheduling to minimize the makespan and workload unbalance among operators. MTSSDRC is a complex problem that needs to integrate two types of scheduling, i.e., job sequencing on the machines and task sequencing, which includes setup, unloading, and moving, by the operators. Since there are two resources, one may be busier than the other. Task sequencing should be prioritized if the operator is very busy, otherwise, we should accentuate the job sequencing. The existing NSGA-II variant prioritizes the machine assignment over the operator. Therefore, its performance is not so well when the operator-to-machine ratio is small. Thus, this proposed research develops two new NSGA-II variants identified by their modified decoding schemes. They posit the operator more important or at least equal to the machine. To the best of our knowledge, this research is the first to analyze MTSDDRC based on the operator-to-machine ratio. The essential finding insists that each variant fits the specific ratio. The new ones are promising for cases with a ratio ⩽0.5. Otherwise, the existing variant is still recommended. Besides, one of the new decoding schemes performs well for all ratio, but not the best.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Complex problems,Decoding scheme,Dual resource constrained,Job sequencing,Machine assignment,Makespan,Non dominated sorting genetic algorithm ii (NSGA II),Task sequencing[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Decoding schemes,Makespan,MTSSDRC scheduling,NSGA-II,Workload unbalance[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]The first author would like to acknowledge financial support from the Hitachi Global Foundation in the form of a scholarship for enrolment in the doctoral program at Sophia University, Japan.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1016/j.eswa.2020.113754[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]