Designing an Energy-Efficient Transportation Network to Transport Perishable Crops: An Aggregated VRP and X-means Clustering Approach

Abstract

Almost all perishable crops deteriorate due to improper and tardy transportation and storage. Vehicle Routing Problem, or VRP, might be of great aid since it takes into account a number of aspects of any transportation and storage issues and optimizes them in such a way as to reduce the overall cost of the carrier. This study attempts to widen the scope of the commonly used VRP model by including traffic and energy consumption features and transforming it into the Aggregated Vehicle Routing Problem (AVRP). Traditional VRP focuses on minimizing distance. Generally, it is unable to find out the optimal number of aggregation points required to serve a system. So, cost optimization of the AVRP approach was designed with two specialized steps. Firstly, the destination data are divided into multiple clusters employing the X-means clustering. And then the best route was found to execute the delivery thus minimizing cost, required time, and carbon footprint. The study was implemented on the Chattogram zone and discovered that the optimal number of aggregation points (AP) required to serve Chattogram is only three namely- AP 1, AP 2, and AP 3. VRP analysis was stretched further with AVRP model using AP 1 and found to reduce the operating cost by 10.96%.

Keywords

• Perishable Crops
• Aggregated Vehicle Routing Problem
• X-means Clustering
• Aggregation Points
• Cost Optimization