Abstract
Freight railroad operations involve complex classification and train formation decisions. Optimization with respect to these decisions can be quite difficult due to discrete and non-linear characteristics of the problem. The train formation plan is one of the important elements of railroad system operations. While mathematical programming formulations and algorithms are available for solving train formulation problem but CPU time required for their convergences is excessive. In this paper, 0-1 bi-level Linear Programming (BLP) is examined for obtaining good solutions with reduced complexity for block container trains formation plan (BCTFP). The minimum spending of container hour is taken as linear step function for optimization of the train formation plan. Cooperative multi-colony genetic algorithm (GA) is proposed for the solution of the block container train formation plan. Finally, the main contribution of the paper is to show the reduced complexity of the algorithm. The efficiency of the algorithm is also shown for convergence to global optimum.
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