关键词: 混合流水车间, 绿色生产调度, 不相关并行机, 运输时间, 多目标麻雀搜索算法

Abstract: Aiming at the influence of transportation time on green production scheduling of mixed flow workshop,the maximum completion time,production energy consumption and production cost were taken as optimization objectives. An Improved Multi-Objective Sparrow Search Algorithm (IMOSSA) was proposed to solve the problem. The fitness values of the population were divided by reference to non-dominated ordering,the quality of the solution set was improved by introducing sine-cosine strategy,and the convergence speed and global search ability of the solution set were improved by adding polynomial mutation operators and Levy flight,so as to avoid falling into local optimality. Then 16 test examples were designed to compare IMOSSA with other multi-objective optimization algorithms to verify the superiority of IMOSSA solution. Finally,taking an actual production workshop as an example,the production scheduling was divided into four modes to prove the practicability of the algorithm.

Key words: mixing flow shop, green production scheduling, unrelated parallel machines, transit time, Multi-Objective Sparrow Search Algorithm (MOSSA)