Golden eagle optimizer-based multi-objective optimization model for scheduling construction projects

This study presents a multi-objective optimization model based on the Golden Eagle Optimizer (GEO) that can simultaneously address all of the defined and quantifiable objectives of a construction project. The model's practicality, accuracy, and effectiveness were evaluated in an example project. Furthermore, mathematical and Particle Swarm Optimization (PSO)-based models were developed for the same purpose. Then, these models were applied to the same example project, and the results were compared to the results of the proposed model. The key results of this study are: (1) the optimal compromise solutions differ depending on the objectives addressed and the number of objectives, (2) when there are more than two objectives in an optimization problem, each solution must be evaluated as a whole, not one at a time, and (3) the proposed model obtained exactly the same optimal compromise solution as the mathematical model in an extremely short time when compared to both the mathematical and PSO-based models.