Abstract. The Covid-19 virus outbreak as an epidemy had caused a strong market reaction to the shares listed on the Indonesia Stock Exchange, as the concerns of shareholders over the government policies. Therefore, to buid a portfolio, it is necessary to calculate optimal the proportion of shares. In this study, a multi-objective optimization will be carried out on six food and beverage companies shares listed on the Indonesia Stock Exchange during March-July 2020. The multi-objective approach on the portfolio solves two optimization problems at once: maximizing expected return and minimizing risk based on investor preferences. Mathematically, the multi-objective approach is multivariable function with equality constraints, which can be solved using the Lagrange multiplier method. The study shows that different risk coefficient will generate different optimum stock proportion. Optimum portfolio with the highest risk (risk coefficient k = 0.01) generate the highest expected return, while optimum portfolio with the lowest risk (risk coefficient k = 1000) generate smallest expected return.Keywords: Optimization, portfolio returns, multi-objective approachAbstrak. Wabah virus Covid-19 sebagai epidemi turut mempengaruhi respon pasar terhadap saham berbagai perusahaan terdaftar di Bursa Efek Indonesia seiring kekhawatiran para pemegang saham atas kebijakan yang akan dikeluarkan pemerintah. Karenanya, dalam penyusunan portfolio, perlu adanya perhitungan proporsi saham yang memberikan return optimal. Pada penelitian ini, dilakukan optimalisasi pada enam saham perusahaan makanan dan minuman yang terdaftar di Bursa Efek Indonesia pada bulan Maret-Juli 2020. Pendekatan multiobjektif pada portofolio menyelesaikan dua masalah optimasi sekaligus: memaksimumkan expected return dan meminimumkan  risiko sesuai preferensi investor. Secara matematis, pendekatan multiobjektif adalah masalah pencarian nilai ektrem fungsi peubah terkendala yang dapat diselesaikan dengan metode pengali Lagrange. Hasil penelitian menunjukkan proporsi saham optimal dengan tingkat risiko terbesar (k = 0.01) menghasilkan expected return portofolio terbesar, tingkat risiko terkecil (k = 1000) menghasilkan expected return terkecil.Kata Kunci: Optimasi, return portofolio, pendekatan multiobjektif