Hybrid Grey Wolf Algorithm for Energy-Efficient Scheduling with Sequence-Dependent Setup Times: A Case Study

Abstract

Abstract Non-renewable energy consumption is one of the dominant factors in global warming. The industrial sector has a significant contribution to this problem. At present, the company is required to carry out efficiency, especially energy consumption, because the industry contributes to the most significant energy consumption. One effort to minimize energy consumption in the industrial sector is with proper scheduling. This research attempts to develop the Hybrid Grey Wolf Optimizer (HGWO) Algorithm to complete Energy-Efficient Scheduling (EES) on the Permutation Flow Shop Scheduling Problem (PFSP). This study considers Sequence-Dependent Setup Times on the PFSP problem. A case study was used to resolve EES on PFSP problems. The HGWO parameter experiment was also used to test the parameters in the case study solving. This research also compares HGWO with several popular procedures. The comparison of algorithms shows that the results of the HGWO algorithm are more competitive for completing EES in PFSP problems.