An i-DMSS Based on Bipartite Matching and Heuristics for Rental Bus Allocation

Abstract

Faced with the imminent retirement of two senior employees who used to make decisions on bus allocations to customers manually, a bus rental company in Seoul, South Korea, asked us to develop a DMSS (decision-making support system) to help the young fresh graduate employee who will be taking over this job from them. Practice has shown that allocation and routing decisions made manually by human operators with long experience are usually nearly optimal, and it is very hard to beat those decisions using a computerized DMSS. Therefore the company asked us to design an i-DMSS (intelligent DMSS) that can help the new decision maker to reach decisions comparable in quality to those made by the retiring pair of senior decision makers. In this paper we discuss this decision problem, its context, the models we used to solve it, the algorithms we used in the i-DMSS to solve these models, and how this i-DMSS is used to make the decisions daily. The i-DMSS is based on bipartite matching and transportation algorithms and heuristics, and produces solutions 10–20% more economical than the manual decisions.