In the management of a construction project, the project duration can often be compressed by accelerating some of its activities at an additional expense. This is the so-called time-cost trade-off (TCT) problem, which has been studied extensively in the project management literature. TCT decisions, however, are complex and require planners to select appropriate resources for each project task, including crew size, equipment, methods, and technology. As combinatorial optimization problems, finding optimal decisions is difficult and time consuming considering the number of possible permutations involved. In this paper, a practical model for TCT optimization is developed using the principle of genetic algorithms (GAs). With its robust optimization search, the GAs model minimizes the total project cost as an objective function and accounts for project-specific constraints on time and cost. To maximize its benefits, the model has been implemented as a VBA macro program. This automates TCT analysis and combines it with standard resource-management procedures. Details of the proposed TCT model are described and several experiments conducted to demonstrate its benefits. The developments made in this paper provide guidelines for designing and implementing practical GA applications in the civil engineering domain.Key words: computer application, time-cost trade-off, construction management, genetic algorithms, and optimization.
Utility of Genetic Algorithms for Solving Large-Scale Construction Time-Cost Trade-Off Problems
