【作者】 陈鹏；

【导师】 李新宇；

【作者基本信息】 华中科技大学 ， 工业工程， 2017， 硕士

【摘要】 车间调度是制造系统中的一个重要环节,因此研究车间低碳调度对于实现低碳制造具有重要的意义,而目前低碳调度研究的评价指标较少、低碳调度求解方法缺乏,同时车间类型也并不丰富,因此对于车间低碳调度的研究需要更加深化。本文针对以效率、能耗、噪声、为优化目标的车间低碳调度问题,设计了混合回溯搜索算法(HBSA),最后通过设计不同规模的算例对HBSA的有效性进行验证与分析。首先,针对考虑空闲时间能耗的置换流水车间低碳调度问题模型,设计了混合回溯搜索算法(HBSA)。根据具体问题设计了编码解码、交叉、变异等操作,重构了解空间;并将回溯搜索算法与NEH、局部搜索(LS)、模拟退火(SA)等策略结合,设计了算法的混合策略。用MATLAB编程实现了该混合算法,将该算法应用于29个测试算例,并把HBSA求得的结果与分支定界法(B&B)和遗传算法(GA)进行比较,计算结果显示了HBSA具有较好的性能。其次,针对机器加工转速可选的作业车间低碳调度问题模型,设计了混合回溯搜索算法(HBSA)。根据具体问题设计了编码解码、交叉、变异等操作,重构了解空间;并将回溯搜索算法与局部搜索(LS)和模拟退火算法(SA)结合,设计了算法的混合策略。用MATLAB编程实现了该混合算法,将该算法应用于3个不同规模的算例,并把HBSA求得的结果与GA进行比较,计算结果显示了HBSA具有较好的性能。然后,针对柔性作业车间低碳调度问题模型,设计了混合回溯搜索算法(HBSA)。根据具体问题设计了编码解码、交叉、变异等操作,重构了解空间;并将回溯搜索算法与局部搜索算法(LS)和模拟退火算法(SA)想结合,设计了算法的混合策略。用MATLAB编程实现了该混合算法,将该算法应用于3个不同规模的算例,并把HBSA求得的结果与GA进行比较,计算结果显示了HBSA具有较好的性能。最后,总结了本文的工作并进行了研究展望。更多还原

【Abstract】 Workshop scheduling is an important part of the manufacturing system,so the study of low-carbon shop scheduling for the realization of low-carbon manufacturing is of great significance.However the current low-carbon scheduling researches lack indicators and low-carbon scheduling solutions,while the workshop type is not rich,so the study of workshop low-carbon scheduling needs to be more deepened.In this paper,a hybrid backtracking search algorithm(HBSA)is designed to solve low-carbon scheduling problem which considers the efficiency,energy consumption and noise as the optimized objective.Finally,the validity of HBSA is verified and analyzed by designing cases with different scales.Firstly,a hybrid backtracking search algorithm(HBSA)is designed for the low-carbon scheduling problem model of permutation flow shop considering idle time energy consumption.According to the specific problems,the code/decoding,crossover and mutation and so on operators are designed to reconstruct the solution space.The backtracking search algorithm is combined with NEH,Local Search(LS)and Simulated Annealing(SA)to design a hybrid strategy.The algorithm is applied to 29 test cases,and the results obtained by HBSA are compared with branch and bound method(B&B)and genetic algorithm(GA).The results show that HBSA has better performance.Secondly,a hybrid backtracking search algorithm(HBSA)is designed for the low-carbon scheduling model of the job shop with spindle speed flexible.According to the specific problems,the code/decoding,crossover,mutation and so on operators are designed to reconstruct the solution space.Combining the backtracking search algorithm with Local Search(LS)and Simulated Annealing(SA),the hybrid strategy is designed.The algorithm is applied to three cases with different scales,and the results obtained by HBSA are compared with GA.The results show that HBSA has better performance.Then,a hybrid backtracking search algorithm(HBSA)is designed for the low-carbon scheduling problem model of flexible job shop.According to the specific problems,the code/decoding,crossover,mutation and so on operators are designed to reconstruct the solution space.Combining the backtracking search algorithm with the Local Search(LS)and Simulated Annealing(SA),the hybrid strategy is designed.The algorithm is applied to three cases with different scales,and the results obtained by HBSA are compared with GA.The results show that HBSA has better performance.Finally,we summarized the full text and forecasted the future work.更多还原