A genetic algorithm for resource levelling of construction projects

Critical path method (CPM) is commonly used in scheduling of construction projects. However, CPM only considers the precedence relations between the activities and does not consider resource optimization during scheduling of projects. Optimal allocation of resources can be achieved by resource leveling. Resource leveling is crucial for effective use of construction resources particularly to minimize the project costs. However, commercial scheduling software has very limited capabilities for solving the resource leveling problem. In this study a genetic algorithm (GA) is developed for the resource leveling problem. The performance of GA is compared with the performance of Microsoft Project 2010 for several sample projects. The comparisons indicate that the GA outperforms resource leveling heuristic of Microsoft Project 2010 significantly. Furthermore, exact solutions were obtained for the sample problems using linear-integer programming technique. Exact solutions reveal that the algorithm is capable of achieving adequate solutions. Hence, the GA provides a powerful alternative for the resource leveling problem.