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Modified Differential Evolution Algorithm for the Continuous Network Design Problem

机译:求解连续网络设计问题的改进差分进化算法

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摘要

The Continuous Network Design Problem (CNDP) is recognized to be one of the most difficult problems in transportation field since the bilevel formulation of the CNDP is nonconvex. On the other hand, the computation time is crucial importance for solving the CNDP because the algorithms implemented on real sized networks require solving traffic assignment model many times, which is the most time consuming part of the solution process. Although the methods developed so far are capable of solving the CNDP, an efficient algorithm, which is able to solve the CNDP with less number of User Equilibrium (UE) assignments, is still needed. Therefore, this paper deals with solving the CNDP using MOdified Differential Evolution (MODE) algorithm with a new local search and mutation operators. For this purpose, a bilevel model is proposed, in which the upper level problem deals with minimizing the sum of total travel time and investment cost of link capacity expansions, while at the lower level problem, UE link flows are determined by Wardrop's first principle. A numerical example is presented to compare the proposed MODE algorithm with some existing methods. Results showed that the proposed algorithm may effectively be used in order to reduce the number of UE assignments in solving the CNDP.
机译:连续网络设计问题(CNDP)被认为是交通领域中最困难的问题之一,因为CNDP的双层公式是非凸的。另一方面,计算时间对于解决CNDP至关重要,因为在实际规模的网络上实现的算法需要多次求解流量分配模型,这是解决过程中最耗时的部分。尽管到目前为止开发的方法能够解决CNDP,但是仍然需要一种能够用较少的用户均衡(UE)分配来解决CNDP的有效算法。因此,本文使用带有新的局部搜索和变异算子的修正差分进化(MODE)算法解决CNDP问题。为此目的,提出了一种双层模型,其中上层问题处理最小化总旅行时间和链路容量扩展的投资成本之和,而在下层问题上,UE链路流由Wardrop的第一个原理确定。给出了一个数值示例,将提出的MODE算法与现有方法进行了比较。结果表明,所提出的算法可以有效地用于减少解决CNDP时的UE分配数量。

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