A Genetic Algorithm Approach for a Real Life Fleet Size and Mix Vehicle Routing Problem: A Case Study in an Automotive Company

This paper considers the daily vehicle routing problem of an automotive company. The considered problem is a special case of the heterogeneous capacitated vehicle routing problem, the so-called fleet size and mix vehicle routing problem (FSMVRP), which decides on the type and number of vehicles required and minimizes the total cost comprised of hiring cost of vehicles, traveling cost and driver cost, under the service time constraint. First, the problem is formulated as a mixed-integer programming model and its validation is performed using small-sized problem instances. Next, a genetic algorithm (GA) based solution approach is designed and embedded into a user-friendly program developed for solving real problem instances in reasonable computation times. The computational results show that the proposed GA produces high-quality solutions. It also provides the decision maker the opportunity of evaluating alternative fleet compositions and distribution routes using the developed program.

Anahtar Kelimeler: Vehicle routing, fleet composition, mixed-integer programming, genetic algorithm

This paper considers the daily vehicle routing problem of an automotive company. The considered problem is a special case of the heterogeneous capacitated vehicle routing problem, the so-called fleet size and mix vehicle routing problem (FSMVRP), which decides on the type and number of vehicles required and minimizes the total cost comprised of hiring cost of vehicles, traveling cost and driver cost, under the service time constraint. First, the problem is formulated as a mixed-integer programming model and its validation is performed using small-sized problem instances. Next, a genetic algorithm (GA) based solution approach is designed and embedded into a user-friendly program developed for solving real problem instances in reasonable computation times. The computational results show that the proposed GA produces high-quality solutions. It also provides the decision maker the opportunity of evaluating alternative fleet compositions and distribution routes using the developed program.

Keywords: Vehicle routing, fleet composition, mixed-integer programming, genetic algorithm

Topaloğlu Yıldız, Ş. & Çiçekdeş, B. (2019). A Genetic Algorithm Approach for a Real Life Fleet Size and Mix Vehicle Routing Problem: A Case Study in an Automotive Company. Journal of Current Research on Engineering, Science and Technology, 5 (1), 29-46.