Flexible Job Shop Scheduling Optimization for Green Manufacturing Based on Improved Multi-Objective Wolf Pack Algorithm

Green manufacturing has become a new production mode for the development and operation of modern future industries. The flexible job shop scheduling problem (FJSP), as one key core problems in field green process planning, hot topic difficult issue research. In this paper, an improved multi-objective wolf pack algorithm (MOWPA) is proposed solving with transportation constraints. Firstly, model constraints established, which takes maximum completion time total energy consumption optimization objectives. Secondly, proposed, designs individual codes from two levels machine. precedence crossover (POX) used to improve intelligent behavior wolves, optimal Pareto solution set obtained by introducing non-dominated congestion ranking. Thirdly, selected using gray relational decision analysis method analytic hierarchy obtain scheme. Finally, compared other algorithms through variety standard examples. results show that superior terms speed convergence performance solution, shows advantages when FJSPs.