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Genetic Algorithms for Optimization of Resource Allocation in Large Scale Construction Project Management
Journal Title Journal of Computers
Journal Abbreviation jcp
Publisher Group Academy Publisher
Website http://ojs.academypublisher.com
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Title Genetic Algorithms for Optimization of Resource Allocation in Large Scale Construction Project Management
Authors Chen, Rui; Wang, Xing-xia; Huang, Jian-wen
Abstract It is well known that a construction project is the process of resource consumption. Especially for large project, more kinds of resources are involved and the amount is very huge. In construction process of a project, the resource is limited and the time is very urgent, so for large scale project management there are some important subjects such as how to effectively distribute resources between each activities and how to effectively utilize limited resources. Therefore, its of great importance to optimize the allocation of construction resource. This paper analyzes existing problems of resource allocation for large scale project, such as shortest construction duration with limited resource and resource leveling with stationary construction duration. Based on that, the corresponding mathematical optimization model is established and solution method on the basis of genetic algorithm is given. Comparing with traditional methods, better results are given when genetic algorithm is used, which can not only compress project duration in maximum, but also reasonably arrange activity starting time in uncritical path, and adjust the order of resource in different activities, to lower the peak of dynamic resource distribution curve as much as possible and to make resource consumption be in equilibrium state. Application in an engineering case shows that genetic algorithm can solve relative problems of resource allocation optimization in network planning for large-scale project very well and will be widely used in project optimization.
Publisher ACADEMY PUBLISHER
Date 2010-12-01
Source Journal of Computers Vol 5, No 12 (2010): Special Issue: Selected Papers of the IEEE International Conference on Compute
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