Factility location and two-echelon-inventory supply chain models with capacity and carbon conatraints

Abstract

Supply chain management holds great importance for the manufacturing industry. More than 9.5% of the U.S. Gross Domestic Product (GDP) is accounted for by logistics, and over 1.3 trillion U.S. dollars are spent on transportation, inventory, and other logistics-related costs. Supply chain management has become essential to making efficient business decisions, and has become increasingly important in making efficient ecological decisions. More and more companies are implementing ‘green' supply chains in an effort to decrease the ecological footprint of their supply chains. This thesis consists of three parts. In the first part we develop a capacitated multi-echelon joint location-inventory model. A single product is distributed from a manufacturer to retailers through a set of warehouses, the locations of which are to be determined by the model. Lateral supply between the warehouses is not allowed and each retailer is assigned exactly one warehouse. Each warehouse can serve multiple retailers. The model decides where to locate warehouses, assigns retailers to the warehouses, and decides the times between orders at the warehouses and the retailers, so as to minimize the cost of operating the supply chain. For each of the warehouses, the reorder quantity must be within the capacity limit of the warehouse. The model is then analyzed to investigate the effect of the capacity limit on the model. In the second part of this thesis, this model is extended to include a carbon trading mechanism. In the third part of this thesis, we develop a genetic algorithm (GA) to solve the supply chain problems described above. The GA is validated on small-size problems by comparing the solution found using the GA to the optimal solution found using GAMS (General Algebraic Modeling System). A sensitivity analysis is carried out to show the effect of the capacity constraint on the model, and also to investigate the effect of varying the price of carbon credits on the model.

Date of Award	2012
Original language	American English
Supervisor	Ali Diabat (Supervisor)