Treffer: An advanced evolutionary algorithm integrating genetic algorithm and branch and bound for joint maintenance grouping and routing optimization

In recent years, growing international trade and advancements in distributed control, information, and logistics have led to the development of geographically dispersed production systems (GDPS). The GDPS is a production network in which production is carried out across several sites located far apart from each other. Optimizing the maintenance plan for such a system requires considering the potential for grouping maintenance tasks and the impact of maintenance itineraries on transportation costs. A joint optimization between maintenance grouping and routing is essential to reduce both preparation and transportation costs. This paper proposes an advanced evolutionary algorithm integrating the Genetic Algorithm (GA) and Branch and Bound (BAB), called GaB. The proposed algorithm’s effectiveness is demonstrated with a numerical example of a typical GDPS with five sites. Results show a 7.44% cost saving compared to individual maintenance and a 59% reduction in computational time compared to the comprehensive search approach.