Abstract

Purpose – Freight carriers operating in a spot-market environment are faced with uncertain future capacity demand, actual revenues, and properties of freight items. They require information about the expected future consumption of limited capacity to derive suitable request acceptance decisions. The purpose of this paper is to present a new idea to improve the handling of inaccurate information on the weight and volume of upcoming requests. Design/methodology/approach – The authors start with the definition of a new mathematical optimization model as the backbone of a capacity control system. This model is embedded within a rolling-horizon decision-making process involving consecutively arriving requests. Computational simulation experiments are carried out to evaluate the applicability and efficiency of the proposed decision support system. The authors investigate how the new model contributes towards keeping the negative impacts of inadequate forecasts of the expected volume of future requests as low as possible. Findings – In traditional application fields of capacity control (airline ticketing or hotel reservations) the physical extent of a request is always 1 (set/bed/room). In road-based freight transportation the variety of the physical extent of requests is much more complicated and complex. The major finding is that existing capacity control approaches are unable to meet the special requirements of road-haulage. Innovative capacity control features are necessary in order to cope with the higher request portfolio complexity. Originality/value – This paper addresses the requirements of a capacity control system for road-based freight transportation. An innovative decision support system is evaluated. For the first time, the authors present a comprehensive quantitative simulation study dedicated to this complicated decision-making situation.

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