A Distributed Coalition Selection of Distribution Centers for Delivery Stations
Year: 2025
Type: article
Abstract: In modern logistics networks, an essential challenge is determining how delivery stations autonomously select the appropriate distribution center for dispatching their shipments. Traditional optimization approaches often rely on centralized decision-making and global computations, leading to high computational costs and limited adaptability in dynamic environments. To address these limitations, this paper proposes a coalition game-based distributed decision-making algorithm, allowing delivery stations to independently form coalitions and optimize their dispatch strategies. Unlike centralized optimization methods, the proposed approach enables real-time decision-making with reduced computational complexity while maintaining both system-wide efficiency and individual delivery station satisfaction. Extensive Monte Carlo simulations demonstrate that our algorithm achieves 8% higher average delivery station utility than Genetic Algorithms and 11% higher than Particle Swarm Optimization when the scale of the delivery stations is large, whereas maintaining comparable distribution center utility. Additionally, the proposed method reduces computational time by over 50% compared to baseline, making it a scalable and practical solution for real-time logistics scheduling. These results confirm that the coalition game-based framework effectively balances individual autonomy and global efficiency, offering a promising alternative for optimizing decentralized logistics dispatch decisions.
Source: IEEE Access
Authors: Fan Wu, Ming Yu, Jingya Zhang, Yicheng Fan, Ming Li
Institution: Dalian University of Technology
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,075
Funder: Dalian University of Technology
OpenAlex ID: W4412719150