计算机科学
禁忌搜索
工作站
能源消耗
数学优化
利润(经济学)
整数规划
遗传算法
算法
数学
工程类
操作系统
机器学习
电气工程
经济
微观经济学
作者
Wei Liang,Zeqiang Zhang,Tao Yin,Yu Zhang,Tengfei Wu
标识
DOI:10.1016/j.ijpe.2023.108928
摘要
Based on the actual requirements of recycling enterprises, this study proposes a multi-parallel partial disassembly line balancing problem (MPPDLBP). Four objectives, the number of shared workstations, workstation load balancing index, energy consumption, and profit, need to be optimised in MPPDLBP. To address the MPPDLBP, this study further constructs a mixed-integer nonlinear programming (MINLP) model and designs a suitable mechanism of encoding and decoding. Meanwhile, partial disassembly is adopted in this study because recycling enterprises aim for low energy consumption and high profits. In addition, the positions of the best values for each objective are defined as the best disassembly levels. Furthermore, this study proposes a genetic and tabu search algorithm (GATS) for optimising the MPPDLBP effectively. The superior performance of the proposed GATS is verified by comparing it with other effective algorithms in existing literature. Finally, this study optimises a hybrid instance and provides decision-makers with multiple low-energy and high-profit disassembly schemes.
科研通智能强力驱动
Strongly Powered by AbleSci AI