Description: this m file can Find a (near) optimal solution to the Traveling Salesman Problem (TSP) by setting up a Genetic Algorithm (GA) to search for the shortest path (least distance needed to travel to each city exactly once)
Notes:
1. Input error checking included
2. Inputs can be specified in any order, so long as the parameter pairs are specified as a parameter , value Platform: |
Size: 4044 |
Author:宏姬 |
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Description: this m file can Find a (near) optimal solution to the Traveling Salesman Problem (TSP) by setting up a Genetic Algorithm (GA) to search for the shortest path (least distance needed to travel to each city exactly once)
Notes:
1. Input error checking included
2. Inputs can be specified in any order, so long as the parameter pairs are specified as a parameter , value -this m file can Find a (near) optimal solution to the Traveling Salesman Problem (TSP) by setting up a Genetic Algorithm (GA) to search for the shortest path (least distance needed to travel to each city exactly once) Notes: 1. Input error checking included2. Inputs can be specified in any order, so long as the parameter pairs are specified as a parameter, value Platform: |
Size: 4096 |
Author:宏姬 |
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Description: Finds a (near) optimal solution to the Traveling Salesman Problem (TSP) by setting up a Genetic Algorithm (GA) to search for the shortest path (least distance needed to travel to each city exactly once)
Platform: |
Size: 3072 |
Author:阳关 |
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Description: 遗传算法解中国旅行商问题，里面有45个城市，用遗传算法算出近似最优解-Genetic Algorithm for Traveling Salesman Problem in China, there are 45 cities, using genetic algorithms calculate the approximate optimal solution Platform: |
Size: 520192 |
Author:lsk |
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Description: 多旅行商问题(Multiple Traveling Salesperson Problem ,简称MTSP) 讨论的是如何安排m( > 1 ) 位旅行商访问n( >
m ) 座城市,要求每个城市只允许被访问一次时,求解所有旅行商花费的费用和是最小(或最大) 的问题。MTSP 问题其实与单
旅行商问题(Traveling Salesperson Problem ,简称TSP) 相似,但是由于添加了任何城市只要被某一旅行商访问到即可这个附加条
件,因而增加了问题复杂度。在以前使用遗传算法(GA) 研究解决MTSP 问题时,通常采用标准的TSP 染色体和处理方法。现
为解决MTSP 问题给出了一种新的染色体设计和相关的处理方法,并与以往的理论设计和计算性能进行比较。计算测试显
示,新的方法能够获得较小的查找空间,在许多方面,新的方法产生的解空间更好。-Multi-Traveling Salesman Problem (Multiple Traveling Salesperson Problem, referred to as MTSP) discussed the arrangements for the m (> 1)-bit traveling salesman visits n (>
m) cities to require each city to allow only visited once, the solution of traveling salesman to spend all the costs and the smallest (or largest) problems. In fact, with the single issue of MTSP
TSP (Traveling Salesperson Problem, referred to as TSP) is similar to, but added any city as long as the visit by a traveling salesman to be attached to the
Pieces, thus increasing the complexity of the problem. The use of genetic algorithms in the past (GA) to study and solve the issue of MTSP, usually a standard chromosome and the TSP approach. Is
MTSP problem to solve is given a new design and associated chromosome approach and the theory of the previous design and to compare performance. Calculation of the test significantly
Show that the new method can find a smaller space, in many respects, the new met Platform: |
Size: 247808 |
Author:liqiubin |
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Description: SP_GA Traveling Salesman Problem (TSP) Genetic Algorithm (GA)
Finds a (near) optimal solution to the TSP by setting up a GA to search
for the shortest route (least distance for the salesman to travel to
each city exactly once and return to the starting city)
-SP_GA Traveling Salesman Problem (TSP) Genetic Algorithm (GA)
Finds a (near) optimal solution to the TSP by setting up a GA to search
for the shortest route (least distance for the salesman to travel to
each city exactly once and return to the starting city)
Platform: |
Size: 3072 |
Author:gao |
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Description: GA_Traffic
The Traveling Salesman Problem (TSP) is maybe the archetypical problem
in combinatorial optimization. This problem and its generalizations, vehicle
routing problems, have been studied for more than thirty years two entire
monographs are devoted to the subject [34, 26]. Since the TSP is NP-hard,
polynomial-time approximation algorithms are usually studied. However,
usually the approaches to the study of vehicle routing problems adopt an
offline point of view: the input is entirely known beforehand. In many
applications, this is actually not the case since the instance becomes known
in an online fashion, time after time. Even determining when the instance
is completely given could be impossible. The need for an online model then
arises naturally.-GA_Traffic
The Traveling Salesman Problem (TSP) is maybe the archetypical problem
in combinatorial optimization. This problem and its generalizations, vehicle
routing problems, have been studied for more than thirty years two entire
monographs are devoted to the subject [34, 26]. Since the TSP is NP-hard,
polynomial-time approximation algorithms are usually studied. However,
usually the approaches to the study of vehicle routing problems adopt an
offline point of view: the input is entirely known beforehand. In many
applications, this is actually not the case since the instance becomes known
in an online fashion, time after time. Even determining when the instance
is completely given could be impossible. The need for an online model then
arises naturally. Platform: |
Size: 1024 |
Author:gardenia_roses |
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Description: a genetic algorithm example : the traveling salesman problem. C source code, suitable for beginners and genetic algorithm optimization and other kinds of knowledge.
Programming Language:Visual C++, Platform: |
Size: 61440 |
Author:esse |
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Description: 遗传算法求解货郎担问题 虽然有些简单 但是绝对适合初学者学习-Genetic algorithm to solve the traveling salesman problem is simple but absolutely suitable for beginners to learn Platform: |
Size: 132096 |
Author:羊笑笑 |
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Description: 基于遗传算法(GA)的多变量旅行商问题(TSP) ，MTSPV_GA Variable Multiple Traveling Salesman Problem (M-TSP) Genetic Algorithm (GA)
Finds a (near) optimal solution to a variation of the M-TSP (that has a
variable number of salesmen) by setting up a GA to search for the
shortest route (least distance needed for the salesmen to travel to
each city exactly once and return to their starting locations)
-Based on genetic algorithm (GA) multivariate traveling salesman problem (TSP), MTSPV_GA Variable Multiple Traveling Salesman Problem (M-TSP) Genetic Algorithm (GA) Finds a (near) optimal solution to a variation of the M-TSP (that has a variable number of salesmen) by setting up a GA to search for the shortest route (least distance needed for the salesmen to travel to each city exactly once and return to their starting locations) Platform: |
Size: 4096 |
Author:赵元 |
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Description: 基于遗传算法的旅行商问题，求最小路径，java图形界面实现-Traveling salesman problem based on genetic algorithms for the minimum path, java graphical interface to achieve Platform: |
Size: 328704 |
Author:薛** |
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Description: TSP_GA Traveling Salesman Problem (TSP) Genetic Algorithm (GA)
Finds a (near) optimal solution to the TSP by setting up a GA to search
for the shortest route (least distance for the salesman to travel to
each city exactly once and return to the starting city)
Summary:
1. A single salesman travels to each of the cities and completes the
route by returning to the city he started from
2. Each city is visited by the salesman exactly once- TSP_GA Traveling Salesman Problem (TSP) Genetic Algorithm (GA)
Finds a (near) optimal solution to the TSP by setting up a GA to search
for the shortest route (least distance for the salesman to travel to
each city exactly once and return to the starting city)
Summary:
1. A single salesman travels to each of the cities and completes the
route by returning to the city he started from
2. Each city is visited by the salesman exactly once Platform: |
Size: 3072 |
Author:XIAOMIN XU |
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Description: 遗传算法的matlab实现，选取了13个城市节点，针对旅行商问题进行的求解。-Genetic algorithm matlab implementation, carried out for the Traveling Salesman Problem Platform: |
Size: 33792 |
Author:万超 |
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Description: 用遗传算法实现旅行商问题，可选择城市数量(Traveling salesman problem is realized by genetic algorithm, and the number of cities can be selected.) Platform: |
Size: 3072 |
Author:tianyunong |
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Search - GA for the salesman problem