This thesis considers a new class of scheduling problems arising in logistics systems in which two different transportation modes are available at the stage of product delivery and the mode with the shorter transportation time charges a higher cost. Each job ordered by the customer is first processed in the manufacturing facility and then transported to the customer. There is a due date for each job to arrive to the customer. In our new scheduling problems, the machine scheduling problem in the manufacturing stage and the transportation mode selection problem in the delivery stage are integrated in order to achieve the global maximum benefit for a company. Three different situations corresponding to three objective functions are discussed respectively. In addition to studying two specia...[ Read more ]

This thesis considers a new class of scheduling problems arising in logistics systems in which two different transportation modes are available at the stage of product delivery and the mode with the shorter transportation time charges a higher cost. Each job ordered by the customer is first processed in the manufacturing facility and then transported to the customer. There is a due date for each job to arrive to the customer. In our new scheduling problems, the machine scheduling problem in the manufacturing stage and the transportation mode selection problem in the delivery stage are integrated in order to achieve the global maximum benefit for a company. Three different situations corresponding to three objective functions are discussed respectively. In addition to studying two special cases: one in which no tardy job is accepted and the other with the maximum tardiness as the tardiness cost, we discuss in detail the problem in which minimizing the sum of the total transportation cost and total weighted tardiness cost is the objective function. A branch and bound algorithm with two different lower bounds is proposed. The effectiveness of the two lower bounds is discussed and compared. A mathematical model that is solvable by CPLEX is also provided. Computational results show that our branch and bound algorithm is superior to CPLEX.