| Title |
Advanced Time-Cost Trade-off Analysis System using Genetic Algorithm |
| Authors |
Bae Tae-Hyun ; Lee Dong-Eun |
| Keywords |
Genetic Algorithm ; Time-Cost Tradeoff Analysis ; Optimization ; Simulation |
| Abstract |
The combination of construction methods selected for the entire activities consisting a network figures up total project cost and duration. Time-Cost Tradeoff Analysis(TCTA) of network is achievable by adjusting the combination. TCTA is an important measure for efficient project scheduling and cost control. This study developed an automated system called "Advanced Time-Cost Tradeoff Optimization system using Genetic Algorithm" which complement limitations of existing systems. This new system automatically runs GA as many times as desired, analyzes the GA output data, and provides the reliability of the global solution. The robustness of existing system is improved by finding different sets of combinations thoroughly, and the new system minimizes the users' involvement by automatically finding and verifying the appropriate options or parameters of GA experiment, which were selected by the user manually based on trial and error fashion or adapted the values published by similar researchers without any verification. The existing TCTA systems are very time consuming in dealing with a large size network. However, the new system would reduce the computational time by applying the optimal number of generation computed and secure the maturity of GA experiment. |