Multiechelon Lot Sizing: New Complexities and Inequalities
Ming Zhao andMinjiao Zhang
Operations Research (forthcoming)
Overview We study a multiechelon lot-sizing (MLS) problem for a serial supply chain where demands can exist at the single production level as well as any of several transportation levels. Assuming stationary production capacity and general cost functions, our mixed-integer programming model integrates production, inventory, and transportation decisions, and generalizes existing literature on many multiechelon lot-sizing models. We answer an open question in the literature by showing that the MLS problem with intermediate demands is NP-hard. We develop polynomial-time algorithms for both uncapacitated and capacitated MLS with a fixed number of echelons. The results outperform many known algorithms developed for various MLS models. We also present families of valid inequalities for MLS that generalize known inequalities. For the uncapacitated case, we develop a polynomial-time separation algorithm and efficient separation heuristics. Finally, we demonstrate the effectiveness of a branch-and-cut algorithm using the proposed inequalities to solve large multi-item MLS problems.
8 | Journal Publications - Financial Times Top 50 Journals
Made with FlippingBook - Online catalogs