A systematic review of hybrid metaheuristic algorithms in time and cost optimization of construction projects

Due to their complex nature, construction projects often experience increases in their time and cost, and optimizing these two aspects has always been one of the main challenges for project managers. In this regard, metaheuristic algorithms, such as genetic algorithms and ant colony optimization, have been proposed as time and cost optimization tools. Currently, researchers have turned to combining these algorithms to overcome their weaknesses or improve their performance. The researchers have demonstrated that combining algorithms can improve outcomes. This article aims to provide a comprehensive review of existing literature that has used hybrid metaheuristic algorithms to optimize time and cost in the construction industry. This article uses a systematic review combined with the snowball method to find the relevant studies. After analyzing and describing various aspects of previous research, this study provides a general framework that future researchers can use to develop new hybrid algorithms for optimizing time and cost in the construction industry.

Keywords:

Hybrid Metaheuristic Algorithms , Time-Cost Optimization , Optimization Framework , Construction Projects