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All Journal International Journal of Advanced Science and Computer Applications
Ji-yuan Chen
Southern Power Grid Supply Chain (Yunnan) Co., Ltd.；
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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Bi-level Programming-Based Optimization of Vehicle Scheduling and Warehouse Operations in Power Logistics Parks yongjie ma; Ji-quan Zhang; Wen-xian Guo; Tian-chi Deng; Yong-xin Jing; Ji-yuan Chen; xian-guang jia
International Journal of Advanced Science and Computer Applications Vol. 5 No. 1 (2026): March 2026
Publisher : Utan Kayu Publishins

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Abstract

To address the coordination between vehicle scheduling and warehouse operations in power logistics parks, this paper develops a bi-level programming model: the upper level optimizes supply chain vehicle scheduling, and the lower level optimizes warehouse inspection and inbound–outbound operations. An improved Carnivorous Plant Algorithm (ISCMA-CPA), integrating self-learning, Cauchy mutation, and mayfly reproduction strategies, is proposed to solve the model. Real-world data from nine vehicles and 45 material types are used for validation. Compared with benchmark algorithms (WOA, IWOA, GA, MA, CPA, AFSC), ISCMA-CPA achieves superior performance: at the upper level, average working time, waiting time, and travel distance are reduced by 35.3%, 75.0%, and 9.3%, respectively, and the objective value decreases by 0.9%; at the lower level, inspection time and path distance decrease by 14.4%, achieving the lowest objective value of 7276.96. The results demonstrate that the proposed bi-level model and algorithm effectively shorten operation time, reduce waiting and travel distances, and realize coordinated optimization of vehicle scheduling and warehouse operations. Overall, this study provides a practical optimization framework that enhances operational efficiency, supports intelligent decision-making, and promotes the green transformation of power material logistics.
Co-Authors Ji-quan Zhang Tian-chi Deng Wen-xian Guo xian-guang jia Yong-xin Jing yongjie ma