New solution methods for the distributed assembly permutation flowshop scheduling problem

In this thesis, Distributed Assembly Line Permutation Flowshop Scheduling Problem, which deals with both distributed manufacturing and distributed assembly systems, is discussed. The purpose of such mixed production problems, which is an important problem of the manufacturing industry, is to minimize the time of obtaining the final products (in other words, to minimize makespan). In this thesis, some different ways to optimize the solution of the problem in question are discussed. Within this framework, new mixed integer linear programming models are proposed in order to solve this problem more effectively. In addition to the heuristic / meta heuristic algorithms currently available in the literature, a new meta heuristic algorithm has been designed and developed in this thesis. Finally, the proposed mathematical models have been compared with the best mathematical model in the literature, using the same datasets and computers with the same features. As a result of the experiments, it has been seen that we have developed a more effective mathematical model than the most effective mathematical model available in the literature. Similarly, the meta heuristic algorithm proposed by us has been statistically compared to the results of the best solutions ever founded for the 1710 data sets generated for the problem. As a result of the experiments, it has been observed that we have developed a more effective meta heuristic algorithm for the solution of the problem than the methods available in the literature so far, and also 40 better results than the best solutions available in the current literature have been found and reported.