Ötken, Çelen NazOrgan, Zeynel BatuhanYıldırım, Elif CerenÇamlıca, MustafaCantürk, Volkan SelimDuman, EkremTeksan, Zehra MelisKayış, Enis2020-07-062020-07-062019-070013-791Xhttp://hdl.handle.net/10679/6709https://doi.org/10.1080/0013791X.2019.1636440The purpose of this study is to find a portfolio that maximizes the risk-adjusted returns subject to constraints frequently faced during portfolio management by extending the classical Markowitz mean-variance portfolio optimization model. We propose a new two-step heuristic approach, GRASP & SOLVER, that evaluates the desirability of an asset by combining several properties about it into a single parameter. Using a real-life data set, we conduct a simulation study to compare our solution to a benchmark (S&P 500 index). We find that our method generates solutions satisfying nearly all of the constraints within reasonable computational time (under an hour), at the expense of a 13% reduction in the annual return of the portfolio, highlighting the effect of introducing these practice-based constraints.engrestrictedAccessarticle64331032100047726280000110.1080/0013791X.2019.16364402-s2.0-85071069728