A Genetic Algorithm for an Integrated Production and Distribution Scheduling Problem with VRP

In this paper، an integrated production and distribution problem with goal of minimizing total weighted number of tardy jobs and transportation costs is considered. There is k customer and a production facility in which jobs are processed and delivered to customers in batches with routing. Delivering the products in batches reduces the delivery cost but it may increase the number of tardy jobs. The mentioned problem which complexity''s is strongly NP-Hard is considered for the first time. In this paper، a mixed integer programing model and a genetic algorithm with a heuristic crossover is developed to solve problem. Full factorial computational test and analysis of variance is performed for evaluation of these two methods. The obtained results show that the genetic algorithm is efficient for the problem.