| Summary: | A work breakdown structure (WBS) can prove to be pivotal to successful project management planning. There are few published studies about the methodologies or tools to develop the appropriate WBS for a project, and those that are available are limited to the specific areas of construction such as apartment-building construction and boiler manufacturing. This research has an emphasis on developing a methodology with higher generalizability, which has the capability to be customized to complex underground projects. To address this issue, a new methodology that employs hierarchical neural networks to develop the WBS of complex underground projects is presented. This methodology has been applied to several tunnel case studies and it has been shown that for a real project, the model is able to generate the WBS and its activities that are comparable to those generated by a project planner. Consequently, it is concluded that these modeling methods have the capacity to significantly improve the WBSs for complex underground projects and improve key project tasks, such as workload planning, cost estimating and scheduling.
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