Abstract
This paper proposes an integrated production and distribution planning optimization model for multiple manufacturing locations, producing multiple products with deterministic demand at multiple locations. There are multiple modes of transport from plants to demand locations and warehouses. This study presents a model which allows decision makers to optimize plant production, transport and warehouse location simultaneously to fulfill the demands at customer locations within a multi-plant, multi-product, and multi-route supply chain system when the locations of the plants are already fixed. The proposed model is solved for sample problems and tested using real data from a cement manufacturing company in India. An analysis of the results suggests that this model can be used for various strategic and tactical production and planning decisions.
Highlights
Extensive research has been performed to optimize production planning, inventory, warehouse location and vehicle routing, which have each been addressed as independent problems by several researchers (Fawcett & Magnan, 2002). Ganeshan and Harrison (1995) classify supply chain functions into four categories - location, production, inventory and transportation
We have developed an integrated production and distribution planning (IPDP) optimization model for a multi-product, multi-plant, multi-location and multi-echelon supply chain environment with multiple transport options including railways and roads
The integrated production and distribution planning model is formulated as a mixed integer programming model to optimize production and distribution allocation within production constraints, obeying transport capacity and the given demand at various customer locations
Summary
Extensive research has been performed to optimize production planning, inventory, warehouse location and vehicle routing, which have each been addressed as independent problems by several researchers (Fawcett & Magnan, 2002). Ganeshan and Harrison (1995) classify supply chain functions into four categories - location, production, inventory and transportation. With recent advances in terms of computational resources, studies featuring an integrated approach to modeling supply chain functions have been proposed (Erengüç, Simpson, and Vakharia 1999, and Kaur, Kanda, and Deshmukh, 2006). As manufacturing and economic conditions have become more dynamic, there has been a greater need to study supply chain functions using an integrated approach in terms of global supply chain operations. This approach is based on integrating the decision making related to various functions - location, production, inventory and distribution allocations - into a single optimization problem. The following section presents a brief review of the literature in the area of integrated supply chain optimization. The final section presents my conclusions and future avenues for research
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