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VNS Metaheuristics to Solve a Financial Portfolio Design Problem: VNS and SVNS Approaches

VNS Metaheuristics to Solve a Financial Portfolio Design Problem: VNS and SVNS Approaches

Copyright: © 2020 |Pages: 17
ISBN13: 9781799818823|ISBN10: 1799818829|ISBN13 Softcover: 9781799818854|EISBN13: 9781799818830
DOI: 10.4018/978-1-7998-1882-3.ch007
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MLA

Fatima Zohra Lebbah. "VNS Metaheuristics to Solve a Financial Portfolio Design Problem: VNS and SVNS Approaches." Algorithms for Solving Financial Portfolio Design Problems: Emerging Research and Opportunities, IGI Global, 2020, pp.148-164. https://doi.org/10.4018/978-1-7998-1882-3.ch007

APA

F. Lebbah (2020). VNS Metaheuristics to Solve a Financial Portfolio Design Problem: VNS and SVNS Approaches. IGI Global. https://doi.org/10.4018/978-1-7998-1882-3.ch007

Chicago

Fatima Zohra Lebbah. "VNS Metaheuristics to Solve a Financial Portfolio Design Problem: VNS and SVNS Approaches." In Algorithms for Solving Financial Portfolio Design Problems: Emerging Research and Opportunities. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-1882-3.ch007

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Abstract

This chapter introduces a VNS-based local search for solving efficiently a financial portfolio design problem described in Chapter 1 and modeled in Chapter 3. The mathematical model tackled is a 0-1 quadratic model. It is well known that exact solving approaches on large instances of this kind of model are costly. The authors have proposed local search approaches to solve the problem, and the efficiency of this type of method has been proved. This chapter shows that the matricial 0-1 model of the problem enables specialized VNS algorithms by taking into account the particular structure of the financial problem considered. First experiments show that VNS with simulated annealing is effective on non-trivial instances of the problem.

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