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Tactical production and distribution planning with dependency issues on the production process
Institution:1. School of Economics and Management, Beijing Jiaotong University, Beijing, China;2. INESC TEC, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal;1. Department of Electrical and Computer Engineering, Naval Postgraduate School, Monterey, CA, USA;2. Office of Naval Research, Arlington, VA, USA;3. US Marine Forces Cyberspace Command, Fort Meade, MD, USA;1. Industrial & Operations Engineering, University of Michigan, Ann Arbor, MI 48109, United States;2. Research & Advanced Engineering, Ford Motor Company, Dearborn, MI 48120, United States
Abstract:Tactical production-distribution planning models have attracted a great deal of attention in the past decades. In these models, production and distribution decisions are considered simultaneously such that the combined plans are more advantageous than the plans resolved in a hierarchical planning process. We consider a two-stage production process, where in the first stage raw materials are transformed into continuous resources that feed the discrete production of end products in the second stage. Moreover, the setup times and costs of resources depend on the sequence in which they are processed in the first stage. The minimum scheduling unit is the product family which consists of products sharing common resources and manufacturing processes. Based on different mathematical modelling approaches to the production in the first stage, we develop a sequence-oriented formulation and a product-oriented formulation, and propose decomposition-based heuristics to solve this problem efficiently. By considering these dependencies arising in practical production processes, our model can be applied to various industrial cases, such as the beverage industry or the steel industry. Computation tests on instances from an industrial application are provided at the end of the paper.
Keywords:Tactical integrated production-distribution planning  Two-stage production process  Sequence dependent setup times and costs  MILP based heuristics
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