This dissertation consists of five submission-ready accepted/submitted papers that address some of the key supply chain problems. Supply chain problems, in terms of the area that they address, can be classified into four major groups: location-allocation problem, transportation problem, manufacturing problem, and inventory problem. In this dissertation, location-allocation and location-routing problems, also called LRPs, are studied using two approaches. In the first approach, presented in Chapters 2 and 3, it is assumed that the value of some parameters of the network are dynamically changing. The objective here is to minimize the total system cost by finding the best location-allocation and routing plan when demand and travel times are dynamic. The dynamic nature of demand/travel time is presented by functions obtained from historical data. In the second approach, the sustainability perspective of the LRP is considered. The objective here is also to minimize the total network cost. However, the total cost is presented in terms of energy cost because of the lack of literature investigating the energy effectiveness of a location-routing plan. Traditionally, the objective function of the LRP is expressed in terms of distance minimization, although distance is not the only factor that contributes to energy consumption in an LRP. This perspective is thoroughly discussed in chapters 4 and 5. Due to the rising price of fuel, industries are concerned more than ever about their transportation costs and modes. In the current economic atmosphere, railway transportation is extremely in demand. Hence, to continue the sustainability part of this dissertation, a rail freight transportation system is investigated. The objective here is to develop a heuristic algorithm that can provide a cost-effective train scheduling plan in a matter of seconds. The main contribution in this section is the integration of a pool of business cost elements and constraints existing in practical train-scheduling problems for obtaining results.

Thesis (Ph.D.)--Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering