Affiliations:
Department of Industrial Engineering, Yildiz Technical University, Barbaros Boulevard, Beşiktaş, Istanbul, Turkey
Correspondence:
[*]
Corresponding author. N. Ceyda Özer, Department of Industrial Engineering, Yildiz Technical University, Barbaros Boulevard, 34349, Beşiktaş, Istanbul, Turkey. Tel.: +90 536 7924754; E-mail: [email protected].
Abstract: City logistics approaches and modeling struggles have a significant role in urban areas in increasing the efficiency of logistics operations and reducing traffic jams and their environmental effects. By developing an effective distribution network for cities, it is possible to compete with the changing world and satisfy flexible customer requirements. In this study, as a real-world case, a city logistics model for Istanbul metropolitan area is designed using multi-objective linear programming that considers the different objectives of the stakeholders in cities by integrating the fuzzy Choquet integral technique in a multi-level distribution network for the automotive spare part industry. This paper makes decisions regarding the amount of product flowing among the echelons, the amount of stock to be kept in the warehouses, and the product delays allowed. While minimizing the transportation cost, holding cost and emission levels during these decisions, the study also aims to maximize the service quality in the warehouses. The model is applied to a logistics network of fifty demand points and thirty time periods which can be considered a middle or large-scale problem. In the model, it is also decided to transport the products with electric or fuel vehicles. In the transport sector, electric vehicles are the key to meet future needs for social, health and other human services. The results are discussed under different scenarios. This research allows the use of such a model in making strategic decisions for the distribution network design in big cities.
Keywords: Fuzzy Choquet integral, electric vehicles, multi-criteria decision making, city logistics, mathematical modeling
