A Multi-Objective Discrete Carnivorous Plant Algorithm for Flexible Job Shop Considering Energy Consumption

In this paper, an effective multi-objective discrete carnivorous plant algorithm (MODCP A) is proposed to solve the multi-objective green flexible job shop scheduling problem (MOGFJSP) with the aim of minimizing makespan, total machine workload and energy consumption simultaneously. First, a hybrid strategy is used to generate the initial population with certain quality and diversity. Second, a novel carnivorous plant and prey grouping method is introduced based on fast nondominated sort and crowding distance. Then, crossover and mutation operators are designed for carnivorous plant and prey to ensure global search efficiency. Additionally, a local search based on common critical operations to enhance the local intensification, where a machine selection strategy is employed to concern the balance between these three objectives. By using Taguchi method of design-of-experiment, suitable parameters are suggested. Finally, simulation results based on the benchmarks demonstrate that MODCPA achieves better performance compared to existing algorithms on MOGFJSP.