Third party logistics (3PL) service transport planning problem optimization model and intuitive solution approach for a retail distribution center using

In today's competitive environment, businesses need to make various decisions in order to optimize and effectively manage their distribution processes. The most important of these works is the creation of the most efficient and efficient vehicle route for the transportation that will take place from the center to the customers. Vehicle Routing Problem (ARP) is the process of determining the routes that create the least cost with the vehicle fleet in order to meet customer demands. Within the scope of the thesis, Multi-Turn and Time Windowed ARP has been studied. Within the scope of the literature, Multi-Turn and Time Windowed ARP are generally encountered in short-lived products with critical lead times. Within the scope of the thesis, a transportation problem in which products are distributed daily to branches under the time window constraint with a fleet of vehicles with certain capacities from a warehouse using a third party logistics service is discussed. The important difference of the problem we are dealing with is that instead of classical route length minimization, it is aimed to minimize the distribution cost that the warehouse pays to a 3pl company and depends on the total number of tours. A heterogeneous capacity fleet is used in distribution and the amount paid per tour is different for different vehicles. Vehicle capacities and branch demands differ. The earliest arrival time of the vehicles to the branches and the latest time to leave the branches are limited in the scope of the problem. However, due to the restrictions depending on the location of the branch, it is not possible for every vehicle to transport to each branch. Vehicles can make more than one tour during the day if necessary and time limits allow. First, an integer programming model was formulated for problem solving. In addition, an heuristic solution approach that can be considered in the greedy search class has been developed for the solution of major problems encountered in practice. Numerical experiments have been conducted to verify the effectiveness of the proposed heuristic. The experimental results show that our proposed algorithm can achieve a near-best solution.