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Global Optimal Routing for Traffic Systems with Multiple ODs using Genetic Algorithm

机译:使用遗传算法具有多个ODS的流量系统的全局最优路由

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The multiple origins multiple destinations routing (MOMDR) problem becomes extremely complicated when considering the traffic volumes on road sections. When solving this kind of problem, only heuristic algorithms have practical values because it is a typical NP-Hard problem. This paper applies Genetic Algorithm (GA) to enhance Sorting- Randomizing-Adjusting-Updating (SRAU) algorithm [1]. The former paper shows that different processing orders of the origin-destinations (ODs) result in different solutions with different performances. Therefore, a heuristic algorithm for finding the best processing order of ODs can optimize SRAU algorithm. In this paper, every processing order of ODs is transformed into a gene/chromosome of the individuals of GA; then the best gene can be found during the evolution of GA; finally, the best gene is transformed back to find the optimal solution of the problem. Sufficient simulations show that the proposed algorithm is more efficient than original SRAU algorithm. Also the consideration of the traffic volumes on the road sections enables the proposed method to apply to real traffic systems.
机译:在考虑道路部分上的交通卷时,多个目的地路由(MOMDR)问题的多个目的地路由(MOMDR)问题变得非常复杂。在解决这种问题时,只有启发式算法只有实用的价值,因为它是一个典型的NP难题。本文应用遗传算法(GA)来增强排序 - 随机调整更新(SRAU)算法[1]。前论文表明,原始目的地(ODS)的不同处理令将导致具有不同性能的不同解决方案。因此,用于查找ODS最佳处理顺序的启发式算法可以优化SRAU算法。在本文中,ODS的每个加工顺序都转化为GA的个体的基因/染色体;然后可以在GA的演变期间找到最好的基因;最后,最佳基因被转换回来找到问题的最佳解决方案。足够的模拟表明,该算法比原始SRAU算法更有效。此外,对路段的交通量的思考使得提出的方法适用于实际交通系统。

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