A Risk-averse Assembly Line Worker Assignment and Balancing Problem with Uncertain Processing Time

Assembly line worker assignment and balancing problem (ALWABP) is committed to assign assembly tasks and workers to work stations that constitute the assembly line. Contrary to the hypothesis that, for each worker, the processing time of task is deterministic, we consider an uncertain version for the ALWABP in which the processing time is a stochastic parameter and exact probability distribution is known. We incorporate the risk measure (e.g., Conditional Value-at-Risk (CVaR)) into the objective function rather than the risk-neutral one based on expectation. The objective of our risk-averse ALWABP is to find an assignment of tasks to workers (to stations) such that the maximum cycle time (i.e., the maximum completion time among all workers) and the value of risk measure are minimum. For the handling problem is of large scale and taking an insight into the stochastic intrinsic nature, we tentatively propose a sample average approximate (SAA) algorithm to approximately solve the ALWABP with risk aversion.