Algorithm development for the vehicle routing problem with loaded distance and route time window

The growth in logistics has resulted in the need for more transportation to manage vehicle routes, which has resulted in the expansion of vehicle route problem (VRP) management along with numerous constraints to meet comprehensive customer needs. The vehicle routing problem with time window is taken into account as different customer requirements create time constraints that are complex and difficult to calculate the optimal route for transport. To find the best solutions to implement these problems, this research presents the development of algorithms for vehicle routing with a time window to assist in the design of freight transport routes. The main objective of this paper is to reduce transportation costs and determine the most comprehensive overall route with the shortest total distance within a time window. This research study is divided into two main parts: Mathematical Modelling using OpenSolver in Microsoft Excel and Programming Language using Genetic algorithms to code in Python along with Asymmetric data. In terms of using Mathematical Modelling, it gives an exact solution. However, due to the large size and complexity of the problem, mathematical methods may not respond to the problem and may take a long time to process. Therefore, using the Programming Language to find the solution is more acceptable because it provides an approximation optimisation solution and takes a shorter processing time by giving the solution close to the best solution, making this method more popular nowadays.Nonetheless, this research study uses Genetic algorithms to be developed in conjunction with the use of Programming Language to find the most suitable solution for the route in transporting products. The solution shows that the development of algorithms for the vehicle routing problem with a time window can find the best solution in terms of reaching the destination within the specified time frame by successfully delivering the product to the customer in the least total distance with a reduction in the number of vehicles, which also results in cost reductions. Therefore, this method is an alternative way to develop a good-performance model and can be used to solve various vehicle routing problems.