Optimization of resource leveling problem under multiple objective criteria using a symbiotic organisms search

Scheduling and resource management are crucial in any construction project. Bad scheduling and resource management can cause delays or cost overruns. Optimization in solving resource leveling is necessary to avoid those problems. A total of nine objective criteria are used to solve resource leveling. Each of them has the same objective, which is to reduce the fluctuation of resource demand of the project. This study compares the performance of symbiotic organisms search (SOS) and particle swarm optimization (PSO) in solving resource leveling problems using separate objective functions. Those nine objective functions generate differing resource demand diagrams since each of them minimizes differing parameters. The results show that SOS produced a better solution in eight of the nine objective functions that are used, and only one objective function produced the same objective value in both SOS and PSO. Further finding reveals that one objective function is better in solving resource leveling than the others.