关键词: 切削参数, 柔性作业车间调度, 低碳制造, 多目标优化, 离散化引力搜索算法

Abstract: To solve the low-carbon optimization problem,the cutting parameters with the flexible job shop scheduling problem was integrated to optimize.The multi-objective integrated optimization model of flexible job shop scheduling was established by considering actual constraints,and an Improved Discrete Gravity Search Algorithm (IDGSA) was proposed to solve the collaborative optimization problem between machine cutting parameters and scheduling scheme.For the characteristics of integrated optimization problems,a new three-layer coding of workpiece sequence-machine sequence-cutting parameter mode was proposed.Different initialization methods were used for different encoding methods to ensure the quality and diversity of the initial solution.According to the three-layer coding characteristics of the integrated optimization problem,a new election mechanism was proposed to select the optimal two-layer sequence,which intersected with the workpiece sequence of elite particles to generate new particles and guide the algorithm to approach the true frontier of Pareto.The multi-point crossover and variable neighborhood search were used to realize the balance of decentralized search with centralized search.The superiorities of the proposed improved algorithm and integration method WERE verified by comparison experiments.

Key words: cutting parameters, flexible job shop scheduling, low carbon manufacturing, multi-objective optimization, discrete gravitational search algorithm