A Genetic Algorithm to Solve Integrated Problem of Selecting and Scheduling Transportation Investment Projects

Document Type : Original Article

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Abstract

One of the most important issues which transportation authorities are always confronted with is investment projects selection. After projects selection, due to resource constraints, selected projects require to be scheduled during the planning horizon. Integration of selecting and scheduling projects in a single model increases the accuracy of the results, but on the other hand increases complexity. In this paper, integrated model of selecting and scheduling transportation investment projects is introduced as a bi-level discrete network design problem. In this model, duration time and annual costs of candidate projects are unknown at first, but they will be determined by solving the model. A new measure to evaluate projects according to the threshold of user satisfaction is developed that in combination with the total travel time form the upper level objective function. Given the great complexity of the exact solution, a genetic algorithm (GA) is proposed to solve the model in a reasonable time. Also to optimize the GA parameters, the Taguchi method has been used. In order to evaluate the performance of the proposed algorithm, Sioux Falls urban transportation network is considered and three sample problems in different scales have been produced. The proposed GA and complete count method used to solve the problems. Numerical results show that proposed GA has an acceptable performance in both solution quality and solution time, especially in the large-scale problem.

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References

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─       رضایی، ع. و اصغرزاده، س. م.(1387) "ارزیابی
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