Multi- Objective Green Vehicle Routing Problem with Uncertain Customer Demand and Carbon Emission Reduction

Vehicle Routing Problem with Time Windows is a combinatorial optimization problem that deals with the fleet of vehicles to find the optimal set of routes while serving the customers at different nodes in a given geographical region within specific time intervals. In this research article, the objective is to minimize the total operational costs, 𝐶𝑂2 emissions and fulfilling the fuzzy customer demand. To calculate the optimal results, a mathematical model consisting of all the restricted constraints is presented and genetic algorithm and particle swarm optimization algorithm is preferred to find the solutions. Moreover, alpha- cut method is applied to calculate the crisp interval for the fuzzy demands. To conclude the experimental results, Solomon dataset (R101) is used to compare the outcomes of genetic algorithm and particle swarm optimization algorithm and it is observed that both genetic algorithm and particle swarm optimization algorithm provides satisfactory results but genetic algorithm provides more optimal outcomes as compared to particle swarm optimization algorithm.