基于新型蛙跳算法的低碳混合流水车间调度

A novel shuffled frog-leaping algorithm for low carbon hybrid flow shop scheduling

针对低碳混合流水车间调度问题(HFSP),提出一种新型蛙跳算法(SFLA)以同时最小化总能耗和总延迟时间.该算法将种群内最差的部分解排斥在模因组之外,运用模因组构建和模因组搜索新策略产生新解,同时利用搜索过程产生的优化数据替换种群中未进入模因组的差解并更新外部档案以提高求解质量.通过算例验证新型蛙跳算法解决该问题的有效性,实验结果分析表明,新型SFLA对于所研究的低碳HFSP具有较强的搜索能力和优势.

For the low carbon hybrid flow shop scheduling problem(HFSP), a novel shuffled frog-leaping algorithm(SFLA) is proposed to minimize simultaneously total energy consumption and total tardiness. Some worst solutions of population are excluded out of memeplexes. New solutions are generated by using new strategies for memeplex construction and memeplex search. Optimization data of search process are utilized to substitute for the worst solutions out of memeplexes and update archive to improve solution quality. A series of examples are given to demonstrate the effectiveness of the new SFLA. The analysis of computational results show that the new SFLA has strong search ability and advantages in solving the low carbon HFSP.