Construction projects are becoming increasingly larger and more complex in terms of size and cost. An optimization tool is necessary for the construction management system to develop the desired construction schedule to save time and cost. However, only a few efforts have been made to deal with the time-cost trade-off problem (TCTP) in the large-scale construction projects, and the existing optimization methods are slightly limited by the trouble of parameter tuning. As TCTP is known to be an NP-hard problem, this paper aims to introduce a new variant of Symbiotic Organisms Search (SOS) algorithm that does not contain control parameters, called DSOS (Discrete Symbiotic Organisms Search) which generates the parasite organism using a heuristic rule based on the network levels. This enhancement helps to improve the exploration phase and avoid premature stagnation. Performances are evaluated on project instances with different numbers of activities varying from 180 to 6300, as well as nine newly generated project instances with 720 activities but different network structures. The obtained results show a good performance of DSOS in terms of robustness and deviation from optimum in comparison with other meta-heuristics and variants of DSOS without using the heuristic rule. The good performance implies that DSOS is sufficient to serve as an effective tool to generate an optimized construction schedule.
- Deadline constraint
- Discrete symbiotic organisms search
- Large-scale construction project
- Time-cost trade-off
ASJC Scopus subject areas
- Computer Science Applications
- Artificial Intelligence