Solving multi-item capacitated lot-sizing problems using variable redefinition
Operations Research
One warehouse multiple retailer systems with vehicle routing costs
Management Science
Solving multi-item lot-sizing problems using strong cutting planes
Management Science
A cutting plane approach to capacitated lot-sizing with start-up costs
Mathematical Programming: Series A and B
Facets and Reformulations for Solving Production Planning With Changeover Costs
Operations Research
Modelling Practical Lot-Sizing Problems as Mixed-Integer Programs
Management Science
Roll assortment optimization in a paper mill: An integer programming approach
Computers and Operations Research
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
OR-based Decision Support in Paper Production Industry
Proceedings of the 2010 conference on Bridging the Socio-technical Gap in Decision Support Systems: Challenges for the Next Decade
Application of fuzzy sets to manufacturing/distribution planning decisions in supply chains
Information Sciences: an International Journal
International Journal of Knowledge-based and Intelligent Engineering Systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper examines a multi-item dynamic production-distribution planning problem between a manufacturing location and a distribution center. Transportation costs between the manufacturing location and the distribution center offer economies of scale and can be represented by general piecewise linear functions. The production system at the manufacturing location is a serial process with a multiple parallel machines bottleneck stage and divergent finishing stages. A predetermined production sequence must be maintained on the bottleneck machines. A tight mixed-integer programming model of the production process is proposed, as well as three different formulations to represent general piecewise linear functions. These formulations are then used to develop three equivalent mathematical programming models of the manufacturer-distributor flow planning problem. Valid inequalities to strengthen these formulations are proposed and the strategy of adding extra 0-1 variables to improve the branching process is examined. Tests are performed to compare the computational efficiency of these models. Finally, it is shown that by adding valid inequalities and extra 0-1 variables, major computational improvements can be achieved.