一种用于PFSP节能优化的混合禁忌搜索算法

A Hybrid Tabu Search Algorithm for PFSP Energy-Saving Optimization

摘要:

为了追求节能减排与净利润最大化，建立一种置换流水车间订单接受与调度模型。禁忌搜索是一类启发式全局搜索算法，传统禁忌搜索对初始解依赖较大，没有对考虑能效的置换流水车间调度问题进行更深入的优化。鉴于问题的复杂性，提出了一种节能混合禁忌搜索算法，结合了NEH构造启发式算法的优势，并在该算法中设计了订单接受与拒绝编码方式、能耗调整与交货期配置策略。最后采用大量随机实例对性能进行分析。实验结果表明，通过上述改进，改善了算法的全局搜索能力与解决复杂模型的寻优能力，节能混合禁忌搜索较单一算法而言性能更优，可以有效增加企业总净利润，降低能源消耗。

Abstract:

To pursue energy conservation, emission reduction and maximization of net profit, a permutation flow shop order acceptance and scheduling model is formulated. Tabu search is a heuristic global optimization algorithm. Traditional tabu search relies on the initial solution, and it is hard to optimize the permutation flow shop scheduling problem considering energy efficiency. Because of the problem complexity, an energy-saving hybrid tabu search algorithm is proposed, which combines the advantages of the NEH construction heuristic algorithm. Besides, the order acceptance and rejection coding method, energy consumption adjustment and due date assignment policy are designed. Finally, a large number of random examples are used to analyze the performance. Experimental results show that through the above improvements, the algorithm's global search capability and the ability to solve complex models are improved. Comparing with the single algorithm, energy-saving hybrid tabu search has better performance, and it can effectively increase the total net profit and reduce energy consumption.