Real option analysis in traffic network design with intelligent algorithm

Xinxin Yu, Shuanwei Cui, Yu Wang, Yi Liu, Xin Yang, Di Wu, Heling Liu, Peng Zhang
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Abstract

In order to ensure the effective use of funds, the government must carry out reasonable traffic planning, in which traffic network design is one of the core contents of traffic planning. The traditional transportation planning has unreasonable factors due to deterministic assumptions. This paper assumes that the demand is a random variable, and then considers the time factor. With the cost recovery and link update as the constraint conditions, the real option is used to solve the problem of the flexibility value of the optimization strategy. The optimization model under uncertainty considering the time factor is given, and the real option is solved by using the LSM method. Genetic algorithm with Monte Carlo is used for network design. The example analysis shows that time factor has a significant impact on network construction decision-making, and real options can effectively describe the flexibility of network construction decision-making.
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智能算法在交通网络设计中的实物期权分析
为了保证资金的有效使用,政府必须进行合理的交通规划,其中交通网络设计是交通规划的核心内容之一。传统的交通规划由于存在确定性假设,存在不合理因素。本文假设需求是一个随机变量,并考虑了时间因素。以成本回收和环节更新为约束条件,利用实物期权求解优化策略的柔性值问题。给出了考虑时间因素的不确定条件下的优化模型,并用LSM方法求解实物期权问题。采用蒙特卡罗遗传算法进行网络设计。算例分析表明,时间因素对网络建设决策有显著影响,实物期权能够有效地描述网络建设决策的灵活性。
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