Improving quality of Crane-Lorry assignments with constraint programming

The ability to maximize service quality while minimizing cost is very important to service-oriented businesses, such as lorry leasing. Very often, the ability to consistently offer higher quality service is the main differentiating factor between a business and its competitors. For lorry leasing businesses, service quality and cost are directly related to how resources-vehicles, cranes, and drivers-are allocated to jobs. The ability to assign the right combination of resources is crucial to daily operations. This paper presents how we modeled this assignment problem as a constraint-satisfaction problem (CSP) and implemented using constraint programming (CP) with an algorithm that we call the crane-lorry optimizing engine (CLOE). CLOE was implemented for the largest crane-lorry company in Hong Kong. Furthermore, plans are generated within seconds compared to close to an hour if done manually. All necessary constraints and criteria are considered systematically. We have experimented with many different types of search heuristics and have analyzed their effects on plan quality. We have found that by considering both the experience of the crane-lorry-driver combination and maximizing on the order assignment, we were able to generate plans that were significantly better than those produced by human planners, and within a substantially shorter time. Although the use of constraint-based assignment techniques is still limited in the vehicle leasing industry, we hope our combination of automated assignment with Internet portal technology that streamlines business-to-business, business-to-consumer, and business-to-employee communications can excite interest in this area.