详情

原文传递 A GENETIC ALGORITHM APPROACH FOR SOLVING THE TRAIN FORMATION PROBLEM.

题名：	A GENETIC ALGORITHM APPROACH FOR SOLVING THE TRAIN FORMATION PROBLEM.
作者：	Martinelli-D; Teng-H
关键词：	TRAIN-FORMATION-PROBLEM; GENETIC-ALGORITHMS; CALIBRATIONS-; VALIDATION-; COMPUTATION-TIME
摘要：	The train formation plan is one of the most important elements of railroad system operations. Although mathematical programming formulations and algorithms are available for solving the train formation problem (TFP), the computational time required for their convergence is usually excessive. At the same time, shorter decision intervals are becoming necessary given the highly competitive operating climates of the railroad industry. Thus, new techniques are needed for generating efficient solutions for the TFP. In this study, the authors present the development of a genetic algorithm (GA) as a possible technique for this problem. The calibration and validation of the GA model are carried out for three different complexity levels of objective functions. It is found that the optimal solutions can be found for all the different formulations while consuming only a small amount of computation time.
总页数：	Transportation Research Record. 1995. (1497) pp62-69 (7 Fig., 8 Tab., 4 Ref.)
报告类型：	科技报告