| Title |
Computational Method for Selecting Optimal Activity Acceleration Methods |
| Authors |
LI, XIANJUN ; Gwak, Han-Seong ; Lee, Dong-Eun |
| DOI |
https://doi.org/10.5659/JAIK_SC.2017.33.6.57 |
| Keywords |
Project crashing ; Genetic Algorithm ; Time-cost function ; Optimization ; Construction method |
| Abstract |
Project schedule compression (or crashing) is frequently required at the planning and construction stages. It is an important technique for all construction participants. Existing studies solved many aspects of this issue. They improved the practicality of the crashing method by considering the diversity and uncertainty of the time-cost function of an activity. This paper presents a system called optimal activity acceleration methods selection system (OAAM). The method generates an activity time-cost function using historical activity acceleration data which administrates overmanning and overtime at job site, defines the productivity efficiency functions which model the effects of overmanning and overtime on activity duration and cost, calculates adjusted activity time and cost attributed to activity acceleration, and identifies optimal activity acceleration alternatives for crashing. It implements the time-cost tradeoff (TCT) using genetic algorithm (GA) and identifies the most economical combination of activity acceleration alternatives to achieve a target schedule compression. A case study is presented to verify the validity of the method. |