Risk-averse assembly line worker assignment and balancing problem with limited temporary workers and moving workers
研究了残疾工人缺勤不确定下，通过临时工和工人移动来平衡装配线的问题，构建了两阶段随机规划模型并设计了遗传算法求解，旨在最小化周期时间和临时工数量的风险加权和。
Assembly line worker assignment and balancing problem (ALWABP) is an important research topic originated from sheltered work centres for disabled, in which workforce is assumed to be heterogeneous due to their disabilities. Since the employment of disabled workers may sustain higher absenteeism rates due to their health, especially under COVID-19, employing temporary workers to fill labour shortage is a crucial issue. In addition, in practice, the movement of workers between stations on assemble lines can increase the flexibility of worker assignment. In this study, we investigate a new risk-averse ALWABP with uncertain disabled worker availability, limited temporary workers and moving workers. The objective is to minimise the risk-averse weighted sum of the cycle time and the number of employed temporary workers. For the problem, a risk-averse two-stage stochastic programming model is formulated. The first stage assigns specific tasks (called fixed tasks) to stations, while the second stage assigns workers and remaining tasks (called flexible tasks) to stations. A genetic algorithm combining K-means clustering approach and variable neighbourhood search (GAKV) is designed. Experiment results show the superiority of the GAKV in terms of solution quality and computation time compared with sample average approximation (SAA). In addition, managerial insights are drawn.