Optimization of Regular Vehicle Routing Problems Based on Set Covering Models

In this paper, we focus on regular vehicle routing problems, in which necessary amount of electric devices are delivered weekly from a central warehouse to a number of regional store by a fleet of vehicles. We develop an optimization method which derives weekly routing plans satisfying several kinds of routing constraints. In this method, a collection of candidate routes are generated by heuristic techniques and a set of the executed routes are selected by a mathematical programming technique based on a set covering model. It has an advantage of the computational costs by restricting the collection of the candidate routes for selection within the feasible and also promising ones. Through some numerical experiments using actual logistic instances and results, the effectiveness and possibility of our proposed method are examined.