元启发式优化在沥青路面管理中的应用

L. R. Vásquez-Varela, F. García-Orozco
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引用次数: 0

摘要

路面工程是岩土工程和交通工程的交叉点,以建筑材料为基础。优化算法在路面工程中有多种应用,强调路面管理的社会经济意义,强调层特性的反计算的复杂性。详细的文献综述表明,优化一直是路面工程中关注的问题。然而,直到最近二十年,计算能力的提高才允许元启发式优化技术的实现,并在研究和实践中取得了有希望的结果。路面管理需要强大的优化工具来解决多目标问题,例如在预算有限的情况下,从网络到项目级别,最小化成本和最大化路面状态。大量的研究集中在遗传算法(GA)上,但新的发展包括粒子智能(PSO、ACO和ABC)。该研究必须超越小型网络,根据机械和可靠性标准改进现有道路基础设施(路面、桥梁)的管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applied Metaheuristic Optimization in Asphalt Pavement Management
Pavement engineering is a crossroads between geotechnical and transportation engineering with a sound base on construction materials. There are multiple applications of optimization algorithms in pavement engineering, emphasizing pavement management for its socioeconomic implications and back-calculation of layer properties for its complexity. A detailed literature review shows that optimization has been a permanent concern in pavement engineering. However, only in the last two decades, the increase in computational power allowed the implementation of metaheuristic optimization techniques with promising results in research and practice. Pavement management requires powerful optimization tools for multi-objective problems such as minimizing costs and maximizing the pavement state from network to project level with constrained budgets. A substantial amount of research focuses on genetic algorithms (GA), but new developments include particle intelligence (PSO, ACO, and ABC). The study must go beyond small-sized networks to improve the management of existing road infrastructure (pavement, bridges) based on mechanistic and reliability criteria.
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