CAJ | 학술논문

将铁路车流径路的优化问题分解为两个:车流排列离散空间中车流排列优化,车流排列的评价计算.在给出车流排列的评价函数的定义后,引入旅行商问题的描述,把车流排列优化问题归约为TSP问题,从而给出了车流排列优化的复杂性分析.引入优先权编码,定义种群个体的适应值函数和相应的遗传操作,给出相应的遗传优化算法,并以实际运营数据为依据,进行仿真计算.通过同禁忌搜索法计算结果比较,遗传算法虽然在解的精度上略逊一筹,但计算工作量小得多,硬件要求也没有禁忌搜索法高.因此,具体选用应以具体情况而定.条件允许,最好将两种算法结合起来使用.
장철로차류경로적우화문제분해위량개:차류배렬리산공간중차류배렬우화,차류배렬적평개계산.재급출차류배렬적평개함수적정의후,인입여행상문제적묘술,파차류배렬우화문제귀약위TSP문제,종이급출료차류배렬우화적복잡성분석.인입우선권편마,정의충군개체적괄응치함수화상응적유전조작,급출상응적유전우화산법,병이실제운영수거위의거,진행방진계산.통과동금기수색법계산결과비교,유전산법수연재해적정도상략손일주,단계산공작량소득다,경건요구야몰유금기수색법고.인차,구체선용응이구체정황이정.조건윤허,최호장량충산법결합기래사용.
Car flow routing optimization is decomposed into two parts:the evaluative function computing of car flow order and the car flow order permutation optimization.The paper first presents the definition of the function to evaluate the order,and then the introduction of the traveling salesman problem.By inducing that the car flow order permutation optimization is traveling salesman problem,an analysis is made of the computational complexity of the car flow routing optimization.The paper also presents a genetic algorithm with designing of priority weight coding,fitness function of population individuals and relevant genetic operation.And simulation results based on a real case are given.Compared with tabu search algorithm, genetic algorithm is lower in computational precision while retaining such advantages of low computing cost and low request of hardware.Therefore,the chioce of the method is based on the real situation,and a combination of the two methods is proposed if permission.