Solution Archive and Its Re-use in Evolutionary Many-objective Facility Control Optimization
Naru Okumura, Yoshihiro Ohta, Hiroyuki Satō · 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS) · 2022
This work proposed an evolutionary building facility control optimization method that re-utilized a promising solution set archived during the optimization process. Evolutionary optimization was suited to solve multi-objective optimization problems. Evolutionary algorithms especially for addressing real-world optimization problems often employed an archive solution set to increase the approximation quality of the Pareto front, the optimal trade-off among objective functions. The proposed method not only employed the archive solution set but also reutilized it for the search. The proposed method updated the searching solution set by the archive solution set at regular intervals. Experimental results showed the re-use of the archived solutions contributed to obtaining solutions that could not be obtained by the conventional method without re-utilization of the archive solution set.