搜索资源列表
VRP
- 用C++设计VRP问题，解决车辆路径问题
VRP
- VRP问题代码 解决车辆路径配送问题 用c++语言开发的-VC VRP
chelianglujingwentiyichuansuanfa
- 车辆路径问题遗传算法matlab程序代码-vrp matlabvrp matlabvrp matlabvrp matlab
AP_For_VRPTW100
- 车辆路径问题的C代码，里面有测试数据和结果分析。-Vehicle routing problem with the C code, there are test data and results analysis.
VRP
- 一个求解车辆路径问题的粒子群算法的源码，用C++编写。-Solving a vehicle routing problem with the particle swarm algorithm source code, using C++ Prepared.
VVRPe
- 车辆路径问题的蚁群算法VRPP-2opt-vrp -Ant colony algorithm for vehicle routing problem VRPP-2opt-vrp
VRP
- 解决车辆路径问题使用矩阵蚂蚁算法 车辆调度问题（Vehicle Routing Problem，VRP）是一个典 型的NP 难题，只有在需点数和路段数较少时才有可能寻求其 精确解，一般情况下，很难得到全局最优解或满意解-Matrix ant algorithm to solve the vehicle routing problem Matrix ant algorithm to solve the vehicle routing problem
ant-algorithem-with-use-of-vb
- 此文件使用vb编程实现蚂蚁算法，从而用来解决车辆路径问题-solve vrp using ant algorithem
VRPBase--No-smallrouteindex
- 禁忌搜索解决待时间窗车辆路径问题，c++基于visio studio 2010平台-Tabu Search Algorithm of VRP
VRP
- 应用遗传算法针对物流配送车辆路径规划问题进行求解，使用MATLAB进行编程-Using genetic algorithm to solve the problem of logistics distribution vehicle routing problem, using MATLAB programming
基于遗传算法的matlab语言车辆路径问题
- 车辆路线问题（VRP）最早是由Dantzig和Ramser于1959年首次提出，它是指一定数量的客户，各自有不同数量的货物需求，配送中心向客户提供货物，由一个车队负责分送货物，组织适当的行车路线，目标是使得客户的需求得到满足，并能在一定的约束下，达到诸如路程最短、成本最小、耗费时间最少等目的。(The vehicle routing problem (VRP) was first proposed by Dantzig and Ramser in 1959, it refers to a cer
vrp
- 车辆路径问题用遗传算法来求解，借助了matlab的程序代码(The vehicle routing problem is solved by genetic algorithm, with matlab program code.)
Genetic algorithm to vehicle routing problem
- 这个代码是采用遗传算法解决车辆路径优化问题，大家一块学习(This code is to solve the vehicle routing optimization problem with genetic algorithm.)
遗传?1
- 遗传算法求解vrp问题，单场库，多车型，实现车辆路径的选择，可用(Genetic algorithm can solve VRP Problem.)
2E-VRP-master1205
- 两层车辆路径问题，可以运行，很不错 matlab程序(Two layer vehicle path problem, can run, very good matlab program)
遗传模拟退火算法求解TSP问题matlab代码
- 解决车辆路径问题，改进的模拟退火和遗传算法，全面详细，适用于解决VRP问题和物流车辆规划(To solve the vehicle routing problem, the improved simulated annealing and genetic algorithm, comprehensive and detailed, suitable for solving VRP problems and logistics vehicle planning)