Optimizing integrated distributed flexible job-shop scheduling and customer order delivery

Abstract

ABSTRACT This study addresses the Distributed Flexible Job-Shop Scheduling Problem (DFJSP) while considering the delivery of customer orders and transportation time. To tackle the problem, a mathematical model is presented, and a novel variant of the Genetic Algorithm (GA), called Time-Travel GA (TTGA), is developed. The optimization objectives include minimizing the total orders’ delivery time to the related customers, reducing transportation and production costs, reducing manufacturing pollution, and maximizing the quality of completed orders. The performance of TTGA is tested by implementing it in a real-life manufacturing setting. Additionally, TTGA results are compared with those of four other algorithms over a set of test problems. Furthermore, the solutions obtained by TTGA are compared with the optimal solutions obtained by a commercial solver for small-size problems. The results of these comparisons collectively demonstrate the promising performance of TTGA in addressing the DFJSP.