Document Type : Original Article
Authors
1
School of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
2
Department of Industrial Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran
10.22034/tri.2022.349148.3066
Abstract
Today, there are many social and environmental pressures to limit the emission of greenhouse gases, especially in the transportation sector. This paper investigates the two-echelon capacitated vehicle routing problem considering the simultaneous pickup and delivery approach. A multi-objective model is developed in order to minimize costs, environmental damage factors, and travel time balance of the transportation fleet to achieve sustainability. To solve this problem, two meta-heuristic algorithms including NSGA II and MOPSO were proposed. To evaluate the performance of the two proposed meta-heuristic algorithms, 15 instance problems were randomly generated. The results of the sample problems were compared in 8 indicators, such as the average of the first to third objective functions, the Number of Pareto Front (NFP), the Maximum Spread Index (MSI), the Spacing Metric (SM), the Mean Ideal Distance (MID), and the CPU run-time (CPU-time) values. The results showed that the NSGA II algorithm has achieved better results than the MOPSO algorithm in the Number of Pareto Front (NFP), the Maximum Spread Index (MSI) and the Spacing Metric (SM). While the MOPSO algorithm has been more efficient than the NSGA II algorithm in achieving the averages of the first to third objective functions, the Mean Ideal Distance (MID) and the CPU run-time (CPU-time). Finally, the MOPSO algorithm has chosen as the best solution method by using the TOPSIS method and obtaining a weight of 0.7061. This article can help managers to benefit by reducing operating costs, reducing harmful environmental effects and the need to pay attention to social criteria in order to gain a competitive advantage throughout the logistics network.
Keywords
Main Subjects
)