LEVERAGING PARTICLE SWARM OPTIMIZATION FOR STRATEGIC DISTRIBUTION CENTER LOCATION INTELLIGENCE - Zhang, Liang Wei; Li, Minghua Chen (International Journal of Civil Engineering and Architecture and Real Estate, 2024)
In an era marked by the relentless advancement of the transportation industry, logistics distribution centers have evolved into pivotal hubs for the turnover, sorting, storage, warehousing, and distribution processing of commodities. These centers represent integral components of the entire logistics chain, linking directly with terminal sales customers. They span procurement, warehousing, transportation, and information services, collectively forming a cohesive business model designed to meet the precise logistics experience expectations of customers. Moreover, they serve as the linchpins that overcome temporal and spatial constraints inherent in the intricate flow of goods. The strategic positioning of logistics distribution centers assumes paramount significance in determining the profitability of logistics companies. A miscalculation in this regard can unleash a series of detrimental repercussions, consuming substantial human and material resources during subsequent logistics activities. Consequently, the meticulous selection of logistics center locations forms the crux of decision-making processes for logistics distribution centers. In light of the imperative task of determining the optimal location for logistics distribution centers, this paper introduces a novel approach. Specifically, we propose a logistics distribution center planning method designed around the utilization of the particle swarm optimization algorithm. This innovative approach aims to enhance both the efficiency and accuracy of identifying the optimal location for distribution centers. By harnessing the computational prowess of this algorithm, we endeavor to propel the logistics industry into an era of enhanced precision, cost-effectiveness, and customer satisfaction.