Solving Urban Routing Problem in Supply Chain by Optimizing PSO Algorithm

Document Type : Original Article


Department of Computer Engineering, Malayer Branch, Islamic Azad University, Malayer, Iran


Addressing the effective distribution of service requests among vehicles in the supply chain stands out as a key hurdle in supply chain management, commonly referred to as vehicle routing with traffic balancing. The optimized vehicle routing, coupled with traffic balancing strategies, emerges as a pivotal factor contributing to heightened customer satisfaction, reduced delivery times, enhanced vehicle utilization, diminished service request demands, and an overall elevation in service quality within the supply chain. To address this, a proposed method involves real-time assessment of service requests and vehicle conditions, enabling balanced routing based on the current operational context. Given the NP-Hard complexity associated with the vehicle routing problem involving traffic balancing in the supply chain, leveraging optimization algorithms, such as PSO, proves to be a more efficient approach. This study introduces a PSO optimization algorithm tailored for the aforementioned challenge. By integrating real-time conditions of service requests and vehicles within the supply chain, the algorithm strategically selects optimal routes for each vehicle and service request. The PSO optimization algorithm undergoes simulation in Python software, undergoes evaluation, and is analyzed alongside comparable routing methods. The assessment outcomes reveal a reduction in distance traveled and total delivery time achieved through the application of the PSO optimization algorithm.


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