New Approaches in Meta-heuristics to Schedule Purposeful Inspections of Workshops in Manufacturing Supply Chains

Abstract

Nowadays, with the growth of technology and the industrialization of societies, work-related accidents, and consequently the threat of human capital and material resources are among the problems of the countries of the world. The most important legal solution in most countries to control occupational accidents and illnesses is to conduct periodic site visits and identify hazardous sites. To the best of our knowledge, no study from the supply chain point of view has been reported to model and address this kind of problem. Thus, this paper is to select the best route that reduces the time elapsed between the workshops and the visit time of the inspectors by using two-tier supply chain simulation coupled with the vehicle routing problem (VRP) to give them more opportunity to visit more workshops. In this study, by considering the number of workshops, the limitation of the number of the existing inspectors and the priority of inspecting the workshops, a bi-objective mathematical model is presented. The main aims are to maximize the number of visited workshops and minimize travel times and workshops visit times. In this study, three meta-heuristics (i.e., SA, SEO and RDA) and two hybrid algorithms are used to address the model. Then, the quality of the meta-heuristics and hybrid algorithms are evaluated and compared by using four metrics. The SEO algorithm provides the best performance; however, in a long time, the hybrid GASA algorithm provides the worst performance. Finally, a real-case study is used to validate the presented model.