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Information Journal Paper

Title

COMPARISON OF PARTICLE SWARM OPTIMIZATION AND TABU SEARCH ALGORITHMS FOR PORTFOLIO SELECTION PROBLEM

Pages

  97-102

Abstract

 Using Metaheuristics models and Evolutionary Algorithms for solving PORTFOLIO problem has been considered in recent years. In this study, by using particles swarm optimization and TABU SEARCH ALGORITHMs weoptimized two-sided risk measures r a,p (R). A standard exact penalty function transforms the considered PORTFOLIO selection problem into an equivalent unconstrained minimization problem. And in finally the historical data from s& p100 from years 2007 through 2009 is used as model input andthen the model was solved and these algorithms were compared.

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    Cite

    APA: Copy

    KAZEMI, M., HEIDARI, A., & LASHKARY, M.. (2017). COMPARISON OF PARTICLE SWARM OPTIMIZATION AND TABU SEARCH ALGORITHMS FOR PORTFOLIO SELECTION PROBLEM. JOURNAL OF NEW RESEARCHES IN MATHEMATICS, 3(9), 97-102. SID. https://sid.ir/paper/257225/en

    Vancouver: Copy

    KAZEMI M., HEIDARI A., LASHKARY M.. COMPARISON OF PARTICLE SWARM OPTIMIZATION AND TABU SEARCH ALGORITHMS FOR PORTFOLIO SELECTION PROBLEM. JOURNAL OF NEW RESEARCHES IN MATHEMATICS[Internet]. 2017;3(9):97-102. Available from: https://sid.ir/paper/257225/en

    IEEE: Copy

    M. KAZEMI, A. HEIDARI, and M. LASHKARY, “COMPARISON OF PARTICLE SWARM OPTIMIZATION AND TABU SEARCH ALGORITHMS FOR PORTFOLIO SELECTION PROBLEM,” JOURNAL OF NEW RESEARCHES IN MATHEMATICS, vol. 3, no. 9, pp. 97–102, 2017, [Online]. Available: https://sid.ir/paper/257225/en

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