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Entropy maximization model for the trip distribution problem with fuzzy and random parameters

机译:带有模糊和随机参数的行程分布问题的熵最大化模型

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摘要

Many trip distribution problems can be modeled as entropy maximization models with quadratic cost constraints. In this paper, the travel costs per unit flow between different zones are assumed to be given fuzzy variables and the trip productions at origins and trip attractions at destinations are assumed to be given random variables. For this case, an entropy maximization model with chance constraint is proposed, and is proved to be convex. In order to solve this model, fuzzy simulation, stochastic simulation and a genetic algorithm are integrated to produce a hybrid intelligent algorithm. Finally, a numerical example is presented to demonstrate the application of the model and the algorithm.
机译:可以将许多行程分布问题建模为具有二次成本约束的熵最大化模型。在本文中,假设不同区域之间的单位流量的旅行成本被赋予模糊变量,并且出发地的旅行产生和目的地的旅行景点被赋予随机变量。针对这种情况,提出了带有机会约束的熵最大化模型,证明了该模型是凸的。为了求解该模型,将模糊仿真,随机仿真和遗传算法进行集成,以产生混合智能算法。最后,通过数值例子说明了该模型和算法的应用。

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