Dispatching rule design for tower crane scheduling in prefabricated construction via genetic programming

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@Article{Yin:2024:autcon,

• author = "Jing Yin and Huanhuan Wang and Jiahao Li and Zhitian Zhang and Shunyao Cai and Wenjun Liu",
• title = "Dispatching rule design for tower crane scheduling in prefabricated construction via genetic programming",
• journal = "Automation in Construction",
• year = "2024",
• volume = "165",
• pages = "105588",
• keywords = "genetic algorithms, genetic programming, Dynamic tower crane scheduling, Dispatching rules, Automatic heuristic generation",
• ISSN = "0926-5805",
• URL = "https://www.sciencedirect.com/science/article/pii/S0926580524003248",
• DOI = "doi:10.1016/j.autcon.2024.105588",
• abstract = "The construction industry is witnessing a shift from traditional cast-in-situ construction to prefabricated construction, aimed at enhancing efficiency and sustainability. However, challenges arise in the transportation and assembly of large precast components. Tower cranes play a pivotal role in these operations, and optimising their service schedule is vital for resource use and project timelines. Traditional tower crane scheduling problems have primarily focused on static scenarios, overlooking the dynamic and uncertain nature of prefabricated construction projects. This paper addresses the complexities of dynamic tower crane scheduling within prefabricated construction using Genetic Programming (GP) to automatically generate Dispatching Rules. Various objective functions were investigated including maximum completion time, tardiness and the number of tardy tasks. The experimental results reveal that GP-generated rules generally outperform benchmark rules, in terms of the best average performance and the discreteness of results. Furthermore, a practical case study validates GP-generated rules, demonstrating superior real-world performance",

}

Genetic Programming entries for Jing Yin Huanhuan Wang Jiahao Li Zhitian Zhang Shunyao Cai Wenjun Liu

Citations