Research on Multi-objective Flexible Job Shop Scheduling Problem Based on Improved Salp Swarm Algorithm

For the multi-objective flexible job shop scheduling problem, a mathematical model with the optimization objectives of minimizing total energy consumption, minimizing production cost, and minimizing penalty value is constructed, and an improved Multi-objective Salp Swarm Algorithm (IMSSA) is designed to solve the problem. The improved algorithm mainly consists of two parts: leaders and followers, where the leader’s position update is implemented in combination with the sine cosine algorithm and the follower’s position update is done based on the linear differential decreasing inertia weight method. In addition, the food source repository is introduced to retain the non-dominated solutions. Finally, the comparative experiments proved the effectiveness of the proposed strategy and the improved algorithm.