A Method for Solving Bi-Objective Green Vehicle Routing Problem (G-VRP) through Genetic Algorithm

In this work, Genetic Algorithm has been used for finding out a solution to the Green Vehicle routing problem with different constraints. Apart from the traditional goal of cost minimization with a time constraint, a problem has also been explored to find a set of routes, one route for each of the vehicles such that both the required energy and the route balances are minimized. A mathematical model has been developed to minimize the total energy consumed and balancing the routes. Hence, authors propose a bi-objective problem to find a set of Pareto-optimal solutions, reasonable trade-offs among different objectives which have been set. The proposed algorithm is based on a scenario where a number of points distributed over a certain area, each of which demands some form of services so that energy consumed and route balancing can be minimized. The service provider has a fleet of vehicles, typically located at a single location called the depot. Each of these vehicles can provide service only to limited number of customers due to capacity constraints. The problem has been solved through tournament selection, greedy crossover and migrating mutation operator. According to the experimental result, the suggested approach is sufficient and the average genetic algorithm performance is good.