CAJ | 학술논문

针对带硬时间窗的关联运输调度问题（ Incident Vehicle Routing Problem with Hard Time Windows ， IVRPHTW），联系实际应用中危险品的车辆路径问题，介绍了混沌遗传算法的基本原理，并对其进行改进，自适应地调整交叉概率和变异概率，引进了模拟退火机制，并用改进的算法来对IVRPHTW求解，然后与遗传算法求解此模型的结果相比较。实例证明该算法求解危险品的关联运输调度问题是可行的，且优于传统的遗传算法。
침대대경시간창적관련운수조도문제（ Incident Vehicle Routing Problem with Hard Time Windows ， IVRPHTW），련계실제응용중위험품적차량로경문제，개소료혼돈유전산법적기본원리，병대기진행개진，자괄응지조정교차개솔화변이개솔，인진료모의퇴화궤제，병용개진적산법래대IVRPHTW구해，연후여유전산법구해차모형적결과상비교。실예증명해산법구해위험품적관련운수조도문제시가행적，차우우전통적유전산법。
Aiming at IVRPHTW (Incident Vehicle Routing Problem with Hard Time Windows ) and VRP(Vehicle Routing Problem) of dangerous goods in practical application , this paper introduces and modifies the fundamental principle of CGA ( Chaos Genetic Algorithm ) adjusting adaptively crossover probability and mutation probability , bringing simulated annealing mechanism in the algorithm, and applying cluster analysis and the modified algorithm to solve IVRPHTW , as well as compared with Genetic Algo-rithm ( GA) .The results show that CGA is feasible to solve IVRP of dangerous goods , and better than GA during the optimization process.