In this thesis, an integrated due date assignment and production and batch delivery scheduling problem with controllable processing times for multiple customers is addressed; therefore, four sets of decisions including due date assignment, resource allocation and production and distribution scheduling are involved simultaneously. This model can also be applied for quoting delivery times when some parts of the jobs may be outsourced. Consider a supply chain scheduling problem in which n jobs have to be scheduled on a single machine and delivered to K customers or to other machines for further processing in batches. A common due date is assigned to all jobs of each customer. The objective is to minimize the sum of the total weighted number of tardy jobs and the total due date assignment, the total resource allocation and the total batch delivery costs. We showed that the mentioned problem is ordinary NP-hard. Four new approaches including an Integer Programming (IP) model, a Heuristic Algorithm (HA), a pseudo-polynomial Dynamic Programming (DP) approach and a Branch and Bound (B am) method, are developed. Also, a Fully Polynomial Time Approximation Scheme (FPTAS) is developed for single customer. Computationaltestareusedto demonstrate the efficiency of the developed methods. In addition, some other related issues were studied.
