Intelligent Optimization Algorithm Based on Minimum Steiner Tree
Abstract
This study explores the application and comparison of the Minimum Steiner Tree (STP) algorithm and the Minimum Spanning Tree (MST) algorithm in optimizing the communication and transportation network in the central area of Kanazawa City. Through a detailed analysis of the classic STP problem and related algorithms, this paper proposes an optimized Ant Colony Optimization algorithm (IACO) and verifies its efficiency on standard datasets. The results show that this algorithm significantly reduces the total connection cost and improves network efficiency and robustness when connecting key nodes. Therefore, this paper suggests that the IACO algorithm has significant application value in urban network planning and recommends further exploration of its potential in larger and more complex networks to optimize the design of urban communication and transportation networks.
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