Collaborative decision making in supply chain scheduling

Managing supply chain systems using effective planning and scheduling solutions is one of the most challenging issues faced by both supply chain practitioners and academic researchers. There are several business drivers across the supply chain. Integrating business processes to handle these drivers further complicates the problem. In recent years, advancements in information technology have allowed companies to use integrated decision strategies in their manufacturing and distribution operations to achieve reduced logistics costs and better customer service. Warehouse management systems (WMS) and transportation management systems (TMS) are now able to provide real-time inventory levels and transportation activities that can be incorporated with the production schedules to promote visibility throughout the entire supply chain.The goals of my dissertation research can be summarized as follows: (1) to develop efficient optimization-based solution techniques for integrated production and distribution operations (2) to provide insights into the impact of collaborative decision making and (3) to further reveal important future research areas in supply chain scheduling. We study integrated production and distribution scheduling decisions in different supply chain configurations. Multiple products are procured, then manufactured and transferred from plants to warehouses and/or customers through capacitated vehicles. The existence of multiple product types and customers may lead to different inventory holding costs and job priorities this feature of the problems is taken into account by assigning product weights. As practically motivated, jobs are also associated with size (volume or storage space required in the transportation unit).We first model the manufacturer's production environment as a parallel machine system. Products are delivered in batches by a single capacitated vehicle to multiple customers (one customer per trip). The scheduling problem can also be viewed as either parallel machines with delivery considerations or a flexible flowshop. Because production schedules could supply ready times for the distribution scheduling problem in a supply chain environment, we then solely focus on distribution part by considering job release times. Jobs become available for pickup at different times and delivered by multiple vehicles. In the above mentioned problems, we study minimizing total weighted completion times in order to capture both customer service levels and different product types. Finally, we extend our studies by investigating two competing objectives: minimizing total transportation costs and total weighted tardiness. Supply chain system involves a single production line and infinite number vehicles. Customers are positioned in different location of the network and a fixed customer-dependent transportation cost incurs for each delivery. Efficient mathematical modeling and near-optimal heuristic approaches are presented for the problems of interest.Traditionally, distribution and production decisions are made by different departments of a company or different parties in the supply chain to achieve their own goals. However, a trade-off exists between the costs and service levels of each supply chain stage associated with each party's objectives and issues. Generally, total cost will be higher when decisions are made independently as compared to coordinated decisions being made for the entire supply chain. As logistics costs can be quite significant relative to product total costs, improving supply chain processes may provide significant savings in the overall supply chain.