Complex and delocalized manufacturing industries require high levels of integration between production and transportation in order to effectively implement lean and agile operations. There are, however, limitations in research and applications simultaneously embodying further sustainability dimensions. This paper presents a methodological framework based on optimization and simulation to integrate aggregate optimized plans for production and multimodal transportation with detailed dynamic distribution plans affected by demand uncertainty. The objective function of the optimization model considers supply, production, transportation, and CO2 emission costs, as well as collaboration over the multimodal network. Bill-of-materials and capacity constraints are included. A feedback between simulation and optimization is used to plan requirements for materials and components. Computational experiments are based on realistic instances. Results demonstrate that the framework can be effectively used to analyze cost-CO2 emission tradeoffs, effects of demand uncertainty, and collaborative distribution strategies on economic and environmental performance of the supply chain.
I E E E Transactions on Industrial Informatics, 2016, Vol 12, Issue 1, p. 417-424
Computer simulation; mathematical programming; production planning; supply chain management