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Short-term booking of air cargo space
Institution:1. Department of Information Systems, Decision Sciences and Statistics, ESSEC Business School, Paris, France;2. Department of Economics and Management, University of Brescia, Brescia, Italy;1. Olayan School of Business, American University of Beirut, Beirut 1107 2020, Lebanon;2. Maroun Semaan Faculty of Engineering, Department of Industrial Engineering, American University of Beirut, Beirut 1107 2020, Lebanon;1. Research Institute of Economics and Management, Southwestern University of Finance and Economics, P.R. China;2. Sauder School of Business, University of British Columbia, Canada;3. Civil Aviation Administration of China, Beijing, P.R. China;4. Institute of Transport and Logistics Studies, University of Sydney, Australia;5. School of Mathematical Sciences, University of Electronic Science and Technology of, P.R. China
Abstract:This paper proposes a stochastic dynamic programming model for a short-term capacity planning model for air cargo space. Long-term cargo space is usually acquired by freight forwarders or shippers many months ahead on a contract basis, and usually the forecasted demand is unreliable. A re-planning of cargo space is needed when the date draws nearer to the flight departure time. Hence, for a given amount of long-term contract space, the decision for each stage is the quantity of additional space required for the next stage and the decision planning model evaluates the optimal cost policy based on the economic trade-off between the cost of backlogged shipment and the cost of acquiring additional cargo space. Under certain conditions, we show that the return function is convex with respect to the additional space acquired for a given state and the optimal expected cost for the remaining stages is an increasing convex function with respect to the state variables. These two properties can be carried backward recursively and therefore the optimal cost policy can be determined efficiently.
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