Abstract Workforce assignment and energy consumption impact greatly on the manufacturing performance. In this work, we study a multi-skilled worker assignment and assembly line balancing problem with the consideration of energy consumption. The problem consists of scheduling products and assigning workers to workstations appropriately under a given cycle time. Two objectives are minimized simultaneously, i.e., (1) the total costs including the processing cost and the fixed cost induced by employing workers, and (2) the energy consumption. A bi-objective mixed-integer linear programming model is formulated and an ϵ -constraint method is adopted to obtain the Pareto front for small-scale problems. For solving large-size problems, a processing time and energy consumption sorted-first rule (PT-EC SFR), a multi-objective genetic algorithm (NSGA-II) and a multi-objective simulated annealing method (MOSA) are developed. Numerical experiments are conducted and computational results show that the designed PT-EC SFR outperforms the other two algorithms in terms of computational time and quality of solutions.

中文翻译：

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环保型多技能工人分配和流水线平衡问题

摘要 劳动力分配和能源消耗对制造绩效影响很大。在这项工作中，我们研究了考虑能源消耗的多技能工人分配和装配线平衡问题。该问题包括在给定的周期时间内安排产品并适当地将工人分配到工作站。同时最小化两个目标，即（1）总成本，包括加工成本和雇佣工人引起的固定成本，以及（2）能源消耗。制定了双目标混合整数线性规划模型，并采用 ϵ 约束方法获得小规模问题的帕累托前沿。对于解决大型问题，处理时间和能耗排序优先规则（PT-EC SFR），开发了多目标遗传算法（NSGA-II）和多目标模拟退火方法（MOSA）。进行了数值实验，计算结果表明，设计的 PT-EC SFR 在计算时间和解的质量方面优于其他两种算法。