Multiobjective Optimization of Time-Cost Trade-Off Using Harmony Search

Completing a project with minimal time as well as minimal cost is a critical factor for scheduling a project. However, because completion speed tends to be correlated with cost (e.g., usually, time can be saved if more workers are hired), the relationship between time and cost is a trade-off. This study employed a phenomenon-mimicking algorithm, harmony search to perform this biobjective trade-off. The harmony search algorithm was applied to two test examples, and good Pareto solutions were obtained when compared with other algorithms, such as the genetic algorithm and the ant colony optimization algorithm. The harmony search algorithm explored only a small amount of total solution space in order to solve this combinatorial optimization problem. The model in this study has obtained good results with a network of up to 18 nodes, however it is anticipated that the model could be useful to solve bigger networks in practice without any difficult problem.