<![CDATA[Multi-objective problems involve multiple objective functions to solve complex problems, and the Nadir Compromise Programming (NCP) method is one way to solve these problems. These problems. Compared to other multi-objective methods, the NCP method has several advantages. Firstly, the weighting in the NCP method can utilize specific parameters to produce an effective optimal portfolio. Additionally, the optimum value of the risk coefficient can be achieved, thereby minimizing large losses. Achieved so as not to cause significant losses. When investing, several essential things need to be considered to achieve an optimal portfolio. These objectives include reducing risk, increasing potential returns, and reducing the amount of capital invested. This study aims to examine the application of the NCP method in solving multi-objective optimization problems for stock portfolios, utilizing monthly stock closing prices from May 2019 to May 2023. In this analysis, the monthly closing prices of 30 stocks that are members of the JII index are analyzed. Six stocks with positive expected returns and the highest stock ratio were selected to form the optimal portfolio. The stocks are BRIS and SIDO. The solution to this multi-objective problem indicates the proportion of funds allocated to the two stocks: BRIS, with a proportion of 0.341147, and SIDO, with a proportion of 0.658853. The analysis also shows that the optimal risk coefficient is 1, the maximum expected return is 0.014569, and the minimum investment capital is Rp.1067.]]>
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