Genetic Algorithm Codes

GA in Solving VRP (Basic)
This simulation was developed to learn Genetic Algorithm and coded in Ms. Net C#. The problem that the author faced was to solve the vehicle routing. In order to implement and visualize how GA perform in solving the problem, the simulator was impemented with a random generated map. Users can actually provide the number of locations he/she wants and how many roads connect to each location, then the map generator will generate a map with the corresponding setting.

Several parameters need to be provided before performing the GA to solve the problem. The parameters are basically the GA needed parameters, such as Population size, Cross-Over Rate, Mutation Rate and Number of Generation. User need to determine the source and destination on the map before simulate the solutions. The system finally will give a path that connect the source and destination location as well as the distant and time using the path. The goal is to get the shortest and fastest route for travel from source to destination.

Furthermore, the simulator actually build in another algorithm - Dijikstra Algorithm. This algoritm is the best and fastest algo in solving shortest path problem. It's actually used to compare wtih GA in solving a specified situation. Simulator also build in with all potential path generation mechanism, but it depend on maps and the source and destnation location that user choose. Sometimes, it will take long time to get all the posible paths generated. However, this mechanism is actually implemented in a thread manner that user actually can generate the potential path and let the simulation run synchronizely. There are a lots of other useful an interesting features implemented in the simulator and the author think it will be too much to state here. So, let download the system and try it! You will discover more....
Related Genetic Algorithm Resource
Related Genetic Algorithm Resource
Copyright © 2005-2015. WebCon Technology Resources. All rights reserved.
Other Related Genetic Algorithm Links