搜索资源列表
vrp.rar
- 编写的基于遗传算法解决VRP问题的源代码,Prepared VRP based on genetic algorithm to solve the problem of source code
vrproblem.rar
- 解决vrp问题用蚁群算法，其中有出错误，还没找出来。,ant colony vrp
chelianglujingwentiyichuansuanfa
- 车辆路径问题遗传算法matlab程序代码-vrp matlabvrp matlabvrp matlabvrp matlab
tsp2matlab
- 该程序试图对具有31个城市的VRP进行求解，已知的最优解为784.1，我用该程序只能优化到810左右，应该是陷入局部最优，但我不知问题出在什么地方。请用过蚁群算法的高手指教。 蚁群算法的matlab源码，同时请指出为何不能优化到已知的最好解-The program attempts to have 31 cities of the VRP is solved, the optimal solution is known as 784.1, I use the program can only
vrp
- vrp为了-vrp with matlab
GA-VRP-MATLAB
- 应用遗传算法求解循环取货的路径优化问题，可以参考一下。-Application of genetic algorithm optimization cycle paths pickup problem。
VRP-1
- this code solves vehicle routing problem using simulated annealing algorithm in matlab. in this code , we create different models and then evaluate them using SA algorithm. one of the advantage of this code , is that code is splitting diff
antcolony
- vrp code with ant colony in matlab
GA-VRP
- 使用MATLAB解决了VRP问题 代码简单易懂-Use MATLAB to solve the VRP straightforward code
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
遗传算法求解vrp问题
- 遗传算法，使用MATLAB进行编程，求解VRP问题(Genetic algorithm for solving VRP problem)
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
蚁群算法Matlab程序
- 求解VRP问题，实用的蚁群算法matlab程序(To solve the VRP problem, a practical ant colony algorithm matlab program)
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.)
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)