Optimization of construction time-cost trade-off analysis using genetic algorithms

In the management of a construction project, the project duration can often be compressed by accelerating some of its activities at an additional expe nse. This is the so-called time-cost trade-off (TCT) problem, which has bee n studied extensively in the project management literature. TCT decisions, however, are complex and require planners to select appropriate resources f or each project task, including crew size, equipment, methods, and technolo gy. As combinatorial optimization problems, finding optimal decisions is di fficult and time consuming considering the number of possible permutations involved. In this paper, a practical model for TCT optimization is develope d using the principle of genetic algorithms (GAs). With its robust optimiza tion search, the GAs model minimizes the total project cost as an objective function and accounts for project-specific constraints on time and cost. T o maximize its benefits, the model has been implemented as a VBA macro prog ram. This automates TCT analysis and combines it with standard resource-man agement procedures. Details of the proposed TCT model are described and sev eral experiments conducted to demonstrate its benefits. The developments ma de in this paper provide guidelines for designing and implementing practica l GA applications in the civil engineering domain.