Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32290
Title: Resource-constrained critical path analysis based on discrete event simulation and particle swarm optimization
Authors: Lu, M
Lam, HC
Dai, F
Keywords: Critical path method
Particle swarm optimization
Resource allocation
Scheduling
Issue Date: 2008
Publisher: Elsevier
Source: Automation in construction, 2008, v. 17, no. 6, p. 670-681 How to cite?
Journal: Automation in construction 
Abstract: The absence of a valid resource-constrained critical path method (CPM) not only hampers the widespread use of mainstream project scheduling software in construction management practice, but also destabilizes the very foundation of any sophisticated, CPM-based time or cost analysis in construction scheduling research. This has motivated us into developing an innovative, fully-automated solution to resource-constrained CPM called the Simplified Simulation-based Scheduling system (short as S3). S3 takes advantage of the simplified discrete event simulation approach (SDESA) and the evolutionary optimization technique called particle swarm optimizer (PSO) to automate the formulation of a resource-constrained schedule with the shortest total project duration. We clarify basic issues of resource scheduling, elaborate on the formation of a CPM simulation model by SDESA, present PSO algorithms, and discuss the PSO solution formulation and simulation-optimization interaction in relation to the development of S3 software. In order to introduce S3 to construction schedulers, we also reference the relevant functionalities and features of Primavera Project Planner (P3) and Microsoft Project, which are applied alongside S3 in two case studies. The first case is a classic textbook example while the second case is based on a real drainage project in Hong Kong. In both cases, S3 eclipses the current CPM software with respect of (1) shortening the total project duration; (2) optimizing provisions of resources of various types; and (3) producing valid total float values to guide schedule implementation.
URI: http://hdl.handle.net/10397/32290
ISSN: 0926-5805
EISSN: 1872-7891
DOI: 10.1016/j.autcon.2007.11.004
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