IJE TRANSACTIONS A: Basics Vol. 22, No. 1 (February 2009) 33-46   

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R. Tavakkoli-Moghaddam*

Department of Industrial Engineering and Department of Engineering Science
College of Engineering, University of Tehran
P.O. Box 11155/4563, Tehran, Iran

H. R. Sayarshad

Department of Industrial Engineering, Mazandaran University of Science and Technology
P.O. Box 734, Bobol, Iran

T. Y. ElMekkawy

Department of Mechanical and Manufacturing Engineering, University of Manitoba
Winnipeg, MB, R3T 2N2, Canada

* Corresponding Author
( Received: December 28, 2007 – Accepted in Revised Form: September 25, 2008 )

Abstract    There is a significant interaction between sizing a fleet of rail cars and its utilization. This paper presents a new multi-period mathematical model and a solution procedure to optimize the rail-car fleet size and freight car allocation, wherein car demands, and travel times, are assumed to be deterministic, and unmet demands are backordered. This problem is considered NP-complete. In other words, the traditional exact optimization approaches cannot solve a real-life size problem of this kind in a reasonable time. To tackle this problem, an efficient meta-heuristic algorithm based on simulated annealing (SA) is proposed. This algorithm works efficiently on a neighborhood search within solution space and probable acceptance of inferior solutions to escape from being trapped in local optima. A number of numerical examples are solved to check for efficiency and validity of the proposed SA algorithm. We conclude that the proposed model and algorithm are useful to identify good strategies for the sizing of rail car fleets and allocation of related cars.


Keywords    Multi-period model, Fleet sizing, Freight car allocation, Railroad transportation, Simulated Annealing



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