Risk-averse two-stage stochastic programming for assembly line reconfiguration with dynamic lot sizes - Li, Yuchen; Liu, Ming; Saldanha-da-Gama, Francisco; Yang, Zaoli (Omega (Oxford), 2024)
In this paper, a comprehensive optimization problem is developed for a composite of an assembly line reconfiguration problem with multiple lines and a capacitated lot-sizing problem. Multiple products are considered, whose demand is uncertain and is dynamically forecasted. The production planner is assumed to be risk-averse, and decisions are made contingent upon the risk preference. To model the problem, a stochastic program with two stages is utilized. A solution approach is devised using a divide-and-conquer algorithm, which incorporates a set of valid inequalities. The effectiveness and efficiency of the proposed solution approach are assessed through a series of computational tests. Finally, a case study focusing on an engine production process is presented, leading to the derivation of several valuable insights. •A joint optimization problem that combines assembly line rebalancing and lot sizing problems.•Stochastic two-stage models are proposed.•Divide-and-conquer algorithm and valid inequalities are utilized.