| Short-term coordinated production and distribution planning is the focus of the research described in this thesis. In their most general form, these problems involve the scheduling of various products in a capacitated manufacturing facility and the distribution of the goods over a distribution network to meet certain demand. Traditionally, both of these related components of a supply chain are treated independently.; The goal of this thesis is two-fold: (i) to develop mathematical techniques for coordination of production and distribution operations, and (ii) to understand the cost and operational impact of coordinated production and distribution decision making. By using mixed integer programming models and techniques, we study various modeling and planning environments of integrated production and distribution. We introduce mathematical formulations for both coordinated and uncoordinated decision making. Through extensive computational studies, we analyze the effect of relevant factors, such as demand, inventory holding cost and production cost. We discuss a common framework for comparing coordinated versus uncoordinated solutions. This framework is then used to test a variety of scenarios of manufacturing and distribution modeling.; We also present a heuristic for solving lot-sizing problems with sequence dependent setups and costs. The algorithm is constructed by combining Benders decomposition and Lagrangian relaxation techniques that exploit the embedded network structures. The experimental results and model characteristics make us believe that this solution technique has important applications for various manufacturing environments. |
