Fuzzy uncertainty management in multi-shift single-vehicle routing problem

Our research deals with the single-vehicle routing problem (VRP) with multi-shift and fuzzy uncertainty. In such a problem, a company con- stantly uses one vehicle to serve demand over a scheduling period of different work shifts. Our issue relies on a routing problem in main- tenance jobs, where a crew executes jobs in different sites. The crew runs during several work shifts but repeatedly returns to the depot before the shift ends. The goal is executing all the activities minimizing the makespan. We examine the impact of uncertainty in driving and mainte- nance processing time on system performance. We realize an Artificial Immune Heuristic to find optimal solutions considering both makespan and overtime avoidance. First, we introduce a framework to assess the uncertainty impact. Then, we produce a numerical company case study to examine the problem. Outcomes present significant improvements are obtained with the proposed approach.