Genetic Algorithm Codes

GA in Solving VRP (C.Map + Vc)
This project contain all the feature available in GA in Solving VRP (Basic) and GA in Solving VRP (C.Map). 2 important additional features for this version: (1) Genetic Algorithm simulation solving shortest path by considering 2 additional constraints which are vehicle capacity and location needs. Consider a vehicle is carrying the supply that needed by each location on a chosen route. (2) Enable user to export the minimum, maximum and mean fitness value data for further analysis.

Genetic Algorithm In Solving Vehicle Routing Problem With Vehicle Capacity Planning Taking The Needs Of All Locations Load Into Consideration. Methodology introduces a new fitness value parameter: Vehicle Capacity Suite to A Route Fitness Value, Fc. Add additional variants into consideration - Vehicle Capacity Planning Taking The Needs Of All Locations Load Into Consideration. System adding a new parameter - vehicle capacity (Kg) and each location contain another variant - Load needed (Kg).

The chosen route by GA not only consider road distance, road speed and condition, but also the maximum location that able to obtain the supply carried by the vehicle (indicate by user for every new simulation). Detail methodolgy that explain how it's fitness value being calculated, how GA analyze it and combine it together with road condition in choosing the best route. Hence, the load that needed for each location is needed. If user input their own map or problem space, then addition information needed to supply for each location (node), #[X coordinate],[Y coordinate], [Location ID], [Load].
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