Abstract
Recently, a lot of studies in which Genetic Algorithm (GA) is applied to Multi-objective Optimization Problems (MOPs), which are called MOGA, have been reported. It is generally important to search a set of Parate solutions in MOPs, and then GA is effective to apply because of the multi-point search. The performance of MOGA, however, decreases with increasing the number of objective functions. Therefore, effective search of MOGA is the important issue in many objective optimization problems. It is one of the effective approaches to assemble some objective functions and reduce the number of them. However, it has not studied the appropriate assembling way and the number of them. The purpose of this study is to grasp the effects of assembling objective functions. This paper studies the effects of assembling when MOGA is applied to simplified Nurse Scheduling Problem (sNSP) and compares two assembling ways based on their meaning and their correlation coefficients.
