• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2011, Volume: 4, Issue: 10, Pages: 1273-1278

Original Article

Using genetic algorithms to solve industrial time-cost trade-off problems


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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