A Novel Hybrid Multi-Verse Optimizer Algorithm for Energy-Efficient Permutation Flow Shop Scheduling Problem

Recently, The issue of energy consumption has become an issue that is often considered, and the manufacturing sector contributes to the most significant proportion of this problem. Energy-Efficient Permutation Flow Shop Scheduling Problem (EEPFSP) is an effective way to solve this problem. This research offers a new algorithm Hybrid Multi-Verse Optimizer Algorithm (HMVO). Siz experiments are presented to minimize total energy consumption. In addition, the Genetic algorithm (GA) and Ant Colony Optimization (ACO) algorithms were used as comparison algorithms. The experimental results show that HMVO requires low iterations to solve small and medium EEPFSP cases. However, the proposed algorithm requires large iterations to solve large case problems. In addition, the HMVO algorithm is more effective than GA and ACO in solving EEPFSP problems.