Applying Petri-net-based Ant Colony Optimization to Resource Allocation: The Case of Waffle Slab Construction
Date Issued
2009
Date
2009
Author(s)
Wu, Yao-an
Abstract
In High-Tech industry, the decision to construct a plant must take the business cycle and capacity requirement of the enterprise into consideration. To facilitate the products getting into market earlier, it often results in the shortening of the duration needed for finishing a plant. The crashing of the scheduling makes the construction less fault-tolerant. Resource planning has significant influence on the activities'' completion, and each activity must be given adequate of resource to assure every task been finished as planned. The purpose of this research is to propose a more precisely workflow network to improve the reliability of scheduling, and use artificial intelligence to reduce the time of searching the best combination of resource.Cleanroom is the most core facility of the High-Tech plan. In a high-tech plant construction, the activity of completing the cleanroom is normally along the project’s critical path. Its completion is crucial to the timely delivery of the company’s products. To timely complete the cleanroom, adequate resource must be supplied to the construction.CPM is a widely used method on project scheduling, but it is inadequate to describe the linkage between resources and tasks. In this research, the Petri-net, a graphical tool in the modeling of workflow management and manufacturing process is proposed to improve the reliability of the workflow simulation. Base on the Petri-net workflow simulation and the collaboration of Ant Colony Optimization(ACO), the optimization time of resource combination is significantly reduced. Meanwhile, the reliability of simulation and optimization are greatly improved.Firstly, a Petri-net workflow model of waffle slab is established, then the field data has been surveyed and imported into the simulation process. The results of field data and Petri-net simulation was then compared. According to the outcome, the result of Petri-net simulation has high relativity with the result of field construction work. This fact verifies that Petri-net is a suitable tool for modelling real construction workflow. Secondly, an artificial intelligence of ACO has been applied to accelerate the planning process of resource allocation. The optimization result shows that the Petri-net based ACO is a fast and reliable method against resource allocation problem.
Subjects
Petri-net
Resource Allocation
Ant Colony Optimization
Workflow Management
High-Tech Facility
CPM
Type
thesis
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