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Issue No:10 Vol.4 |
October-2011 |
ISSN: 0974-5645 |
| RESEARCH ARTICLES |
Viewers & PDF |
| 14. Using genetic algorithms to solve industrial time-cost trade-off problems. Ghorbanali Mohammadi. Indian J.Sci.Technol. Vol. 4, Issue 10, pp: 1273-1278. Domain site: http://www.indjst.org. |
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- Abstract
Time-cost trade-off analysis is one of the most important aspects of industrial project planning and control. There are trade-offs between time and cost to complete the activities of a project; in general, the less expensive the resources used, the longer it takes to complete an activity. Existing methods for time-cost trade-off problems focus on using heuristics or mathematical programming. These methods, however, are not efficient enough to solve large scale CPM problems. This paper presents a Multi-Objective Genetic Algorithm (MOGA) approach to time-cost trade-off problems (TCTP). Finding optimal decisions is difficult and time-consuming considering the numbers of permutations involved. This type of problem is NP-hard, hence attainment of IP/LP solutions, or solutions via Total Enumeration (TE) is computationally prohibitive. The MOGA approach searches for locally Pareto-optimal or locally non-dominated frontier where simultaneously optimization of time-cost is desired. The application of the proposed algorithm is demonstrated through an example project a real life case. The results illustrate the promising performance of the proposed algorithm.
- Keywords: Time-cost trade-off, Genetic Algorithms, project management
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