Integrating purchase and production planning. Using local search in supply chain optimization (Q2760870)

The PhD-thesis deals with the problem of purchase and production planning. The problem is handling through extensions of optimization techniques for more classical production planning problems. Most of the algorithms are eased on local search techniques.NEWLINENEWLINENEWLINEIn Chapters 2-4, the design of production plan and the design of purchase plan are considered separately. The basic model for the production planning problem is the job shop scheduling problem. The main assumptions are that each job consists of a number of operations, which have to be processed in a given order, each on a specified machine. The author handles the problem of finding the starting times for all operations with a tabu search algorithm that generalizes the Nowicki and Smutnicki approach for the classical job shop scheduling problem [\textit{E. Nowicki} and \textit{C. Smutnicki}, Manage. Sci. 42, 797-813 (1996; Zbl 0880.90079)].NEWLINENEWLINENEWLINEThe main goal of designing the purchase plan is to assign all demands to a supplier and to a moment in time in such a way that all constraints are satisfied and the sum of purchase costs and the inventory costs is minimized. A local search algorithm for a purchase lot sizing problem with quantity discount is presented in Chapter 4, and computational results using it is compared with the solutions of two mixed-integer linear programming formulations.NEWLINENEWLINENEWLINEIn the final Chapter 5, the author develops four integrated solution approaches based on the algorithms developed in the earlier chapters. Computational experiments show that solving production and purchase subproblems simultaneously gives the best results.