摘要
为使危险品运输的安全系数最大及运输成本最小,考虑运输者和监管部门对危险品运输路径的不同需求,运用双目标优化方法选择危险品运输的最优路径.将人口密集且短时间内不易疏散的脆弱区域到危险品运输道路的最短安全距离实行量化处理,依据最短距离/人口数的安全系数,以运输成本最低、途径人口密集区的安全系数最大为目标,构建以道路安全系数为约束的双目标混合整数规划模型,并设计基于优先权重的粒子群算法求解模型,通过Matlab平台仿真实现.建立有30个路径节点、20个人口中心的危险品运输网络,并以此作为算例,验证模型与算法的有效性.结果表明,双目标优化模型可得到不同优化组合的运输路径,并且该算法可以获得运输路径优化问题的最优解,可为危险品运输路径问题提供技术支持.
To solve the problem about the maximum safety and minimum transportation cost of hazardous materials transportation,in consideration of different path demand of operators and regulators for transport of dangerous goods,a bi-objective optimization method was used to select the optimal path of hazmat transportation. Quantizing minimum safety distance between vulnerable center and the road of hazmat transportation,according to safety factor of minimum safety distance/dense population,aiming at getting the minimum transportation cost and the maximum safety factor of vulnerable center,a bi-objective mixed-integer program model with a constraint of roads safety factor was set up and the priorities particle swarm optimization algorithm was established by using Matlab simulation platform. The model and algorithm were verified by simulation of the hazmat transportation network with 30 path nodes and 20 population centers. Results show that the bi-objective model can be used to obtain different combination of the optimized path,and the algorithm can seek to optimize the Pareto solution,which could provide technical support for hazmat transportation routing problem.
出处
《大连海事大学学报》
CAS
CSCD
北大核心
2016年第4期112-118,共7页
Journal of Dalian Maritime University
基金
国家自然科学基金资助项目(11301334)
关键词
危险品运输
双目标优化
路径优化
粒子群算法
hazardous materials（hazmat） transportation
bi-objective optimization
route optimization
particle swarm optimization algorithm
