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首页> 外文期刊>Journal of King Saud University >Application of particle swarm optimization to transportation network design problem
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Application of particle swarm optimization to transportation network design problem

机译：粒子群算法在交通网络设计中的应用

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Transportation network design problem (TNDP) aims to choose from among a set of alternatives (e.g., set of new arcs) which minimizes an objective (e.g., total travel time), while keeping consumption of resources (e.g., budget) within their limits. TNDP is formulated as a bilevel programming problem, which is difficult to solve on account of its combinatorial nature. Following a recent, heuristic by ant colony optimization (ACO), a hybridized ACO (HACO) has been devised and tested on the network of Sioux Falls, showing that the hybrid is more effective to solve the problem. In this paper, employing the heuristic of particle swarm optimization (PSO), an algorithm is designed to solve the TNDP. Application of the algorithm on the Sioux Falls test network shows that the performance of PSO algorithm is comparable with HACO.
机译：运输网络设计问题（TNDP）旨在从一组备选方案（例如一组新弧线）中进行选择，这些方案可以最大程度地减少目标（例如总旅行时间），同时将资源消耗（例如预算）保持在其限制范围内。 TNDP被表述为双层编程问题，由于其组合性质而难以解决。经过最近的启发式蚁群优化（ACO），已在苏福尔斯（Sioux Falls）的网络上设计并测试了杂交ACO（HACO），这表明该杂种更有效地解决了这一问题。本文采用粒子群算法的启发式算法，设计了一种求解TNDP的算法。该算法在苏福尔斯测试网络上的应用表明，PSO算法的性能与HACO相当。

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