Journal of Engineering, Project, and Production Management, 2026, 16(5), 2025-311
Fast Logistics Facility-Distribution Optimization Based on IGOA
Associate Professor, College of Business Administration, Zhengzhou University of Science and Technology, Zhengzhou 450064, China, E-mail: wangjinrui7980@126.com
Production Management
Received December 8, 2025; revised January 21, 2026; accepted April 29, 2026
Available online June 17, 2026
Abstract: With the sustained prosperity of global e-commerce and the increasing demand for logistics timeliness, traditional distribution networks face challenges such as low efficiency, high costs, and poor resource allocation. To address these issues, this study proposes a fast logistics facility-distribution optimization method based on an Improved Grasshopper Optimization Algorithm. A multi-objective optimization model integrating facility location selection and vehicle routing planning is constructed, with the dual objectives of minimizing total cost and maximizing customer satisfaction. Customer satisfaction is quantified through a time penalty function and a service attenuation mechanism, incorporating soft time windows and service quality loss costs. The Improved Grasshopper Optimization Algorithm is enhanced via non-dominated sorting and crowding distance computation, along with a hybrid local search mechanism and a differentiated position update strategy to balance global and local exploitation. Experimental results demonstrate that after 30 days of operation, the proposed method achieves a vehicle load rate of 99.6%, an order consolidation ratio of 98.6%, an average delivery time of 5.8 hours, and a delivery cost of 2.1 dollars/order. These findings indicate that the method exhibits strong capabilities in path optimization, dynamic scheduling, real-time responsiveness, and system reliability, offering an intelligent and efficient solution for modern logistics distribution systems. It should be noted that these findings are derived from simulation experiments, and further validation in real-world logistics systems is necessary to confirm their practical applicability.
Keywords: Improved grasshopper optimization algorithm, fast logistics, multi-objective model for logistics facilities-distribution, local search mechanism, differentiated location update strategy.
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Citation: Wang, J. (2026). Fast Logistics Facility-Distribution Optimization Based on IGOA. Journal of Engineering, Project, and Production Management, 16(5), 2025-311.
