The Multi-Depot Vehicle Routing Problem (MDVRP), an extension of classical VRP, is a NP-hard problem for simultaneously determining the routes for several vehicles from multiple depots to a set of customers and then return to the same depot.
The objective of the problem is to find routes for vehicles to service all the customers at a minimal cost in terms of number of routes and total travel distance, without violating the capacity and travel time constraints of the vehicles.
The Genetic Algorithm (GA) is a metaheuristic (a higher-level procedure or heuristic designed to find, generate, or select a heuristic). It is is based on a parallel search mechanism, which makes it more efficient than other classical optimization techniques such as branch and bound, tabu search method and simulated annealing
The algorithm is inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA).
GAs are commonly used to generate high-quality solutions to optimization and search problems by relying on bio-inspired operators such as mutation, crossover and selection.
Survival of the fittest through natural selection
- Generate a set of random solutions
- Repeat until best individual is good enough:
- Test each individual in the set (rank them)
- Remove some bad solutions from set
- Duplicate some good solutions
- Make small changes to some of them