A Genetic Algorithm Developed for a Supply Chain Scheduling Problem

This paper concentrates on the minimization of total tardiness and earliness of orders in an integrated production and transportation scheduling problem in a two-stage supply chain. Moreover, several constraints are also considered, including time windows due dates, and suppliers and vehicles availability times. After presenting the mathematical model of the problem, a developed version of GA called Time Travel to History (TTH) algorithm, inspired from the idea of traveling through history, is proposed to solve the problem. In order to validate the performance of the proposed algorithm, the results of TTH algorithm are compared with two other genetic algorithms in the literature. The comparison results show the better performance of the proposed algorithm. Moreover, the results of implementing the sensitivity analysis to the main parameters of the algorithm show the behavior of the objective functions when the parameters are changed.