A Comparison of Robust Criteria for Vehicle Routing Problem with Soft Time Windows

Abstract

In this study, we focus on robust criteria for vehicle routing problems with soft time windows (VRPSTW). The main objective is to find a robust solution that provides the best for the worst case performance for VRPSTW under uncertain travel times. The robust criteria are used in this study such as absolute robustness, robust deviation, and relative robustness as a basis for comparison. The VRPSTW becomes complex when the travel times are uncertain. This uncertainty can be caused by traffic jams, accidents, or inclement weather conditions. The experiment uses benchmarking problems. The number of scenarios is generated randomly into intervals of travel time, equal to 4, 6, and 8 instances for each problem set. Each set of problem instances can be denoted by the percentage of uncertainty α, equal to 0.2, 0.4, 0.6, and 0.8. This study will demonstrate that the most indicated robust criteria for these situations are robust deviation and relative robustness. The most important part of the decision maker is to determine the uncertainty percentage to cover all uncertainties that need to be considered.