关键词: 低碳策略, 柔性作业车间, 生产调度, 灰狼优化算法

Abstract: To improve the production efficiency and reduce the energy consumption,by analyzing the research status of low-carbon scheduling problem,a mathematical model was established with the criterion to minimize the weighted sum of energy-consumption cost and completion-time cost in flexible job shop.According to the characteristics of the established model,a series of design and improvement were conducted to Grey Wolf Optimization (GWO).In this algorithm,a two-phase encoding/decoding mechanism of individual position and a heuristic-based population initialization method were employed to enhance the quality of initial solutions;a nonlinear adjustment strategy of convergence factor and an individual update method with weight coefficients were developed to act on the evolutionary process;a local search algorithm was embedded into the algorithm to enhance the local search ability.The extensive simulation data demonstrated that the proposed algorithm was effective for solving the low-carbon scheduling problem in the flexible job shop.

Key words: low-carbon strategy, flexible job shop, production scheduling, grey wolf optimization