Impact of Using Multiple Objective Functions on Resource Leveling Using Symbiotic Organisms Search Algorithm

Abstract

The allocation of labor is often a problem that can hinder projects. Optimization is needed in completing resource leveling so that fluctuations in labor requirements can be avoided. This study uses five objective functions to solve resource leveling with the same objective, namely reducing fluctuations in the histogram of labor. This study aims to evaluate the performance and impact of the five objective functions to find out which objective function can produce an efficient histogram of labor and to determine the effect of resource leveling on changes in fluctuations in labor costs. The research used the symbiotic organisms search (SOS) algorithm. The results show that the performance and impact of objective function 4 is more effective in improving the quality of the optimal solution individually and as a whole, resulting in a smoother labor allocation histogram compared to other objective functions so as to improve the efficiency and effectiveness of project implementation.