• Proceedings of the KSR Conference
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• 2011.05a
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• pp.269-276
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• 2011

This paper considers the rail crane scheduling problem with minimizing the sum of the range of order completion time and make-span of rail crane simultaneously. The range of order completion time implies the difference between the maximum of completion time and minimum of start time. Make-span refers to the time when all the tasks are completed. At a rail terminal, logistics companies wish to concentrate on their task of loading and unloading container on/from rail freight train at a time in order to increase the efficiency of their equipment such as reach stacker. In other words, they want to reduce the range of their order completion time. As a part of efforts to meet the needs, the crane schedule is rearranged based on worker's experience. We formulate the problem as a mixed integer program. To validate the effectiveness of the model, computational experiments were conducted using a set of data randomly generated.

• IE interfaces
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• v.24 no.4
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• pp.281-294
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• 2011

This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.238-247
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• 2018

This paper considers the problem of scheduling loading and unloading operations of a crane in a railway terminal motivated from rail-road container transshipment operations at Uiwang Inland Container Depot (ICD). Unlike previous studies only considering the total handling time of containers, this paper considers a bi-criteria objective of minimizing the weighted sum of the total handling time and tenant service time. The tenant service time is an important criterion in terms of terminal tenants who are private logistics companies in charge of moving containers from/to the terminal using their trucks. In the rail-road container shipment yard, the tenant service time of a tenant can be defined by a time difference between beginning and finishing loading and unloading operations of a crane. Thus, finding a set of sequences and time of the crane operations becomes a crucial decision issue in the problem. The problem is formulated as a nonlinear program which is improved by linearizing a nonlinear constraint in the model. This paper develops a genetic algorithm to solve the problem and performs a case study on the Uiwang ICD terminal. Computational experiment results show that the genetic algorithm shows better performance than commercial optimization solvers. Operational implications in terms of tenants are drawn through sensitivity analyses.