MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS: DESCRIPTION, APPLICATION AND PERFORMANCE COMPARISON OF NSGA II AND SPEA 2
MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS: DESCRIPTION, APPLICATION AND PERFORMANCE COMPARISON OF NSGA II AND SPEA 2
Author(s): Florentina-Mihaela Apipie, Genoveva-Mihaela IoanaSubject(s): Methodology and research technology, Accounting - Business Administration, ICT Information and Communications Technologies
Published by: Editura Universitaria Craiova
Keywords: multiobjective optimization problems; portfolio optimization; Markowitz theory; multiobjective evolutionary algorithms; Non-dominated Sorting Genetic Algorithm II; Strength Pareto Evolutionary Alg.;
Summary/Abstract: In this paper we try to find a way to invest efficiently in a portfolio of shares. This is a problem with two objectives to optimized. Multiobjective optimization problems (MOP’s) with contradictory objectives work with a set of solutions which dominate the rest of solutions in comparison with single-objective optimization (SOP) who is trying to obtain the best solution. The main objectives of the paper are to test, compare and evaluate differences of two multiobjective evolutionary algorithms applied on a portfolio of twenty stock market shares listed on Bucharest Stock Exchange. For that, we select Non-dominated Sorting Genetic Algorithm II (NSGA II) and Strength Pareto Evolutionary Algorithm 2 (SPEA 2) to approximate the Pareto Front.
Journal: Revista tinerilor economişti
- Issue Year: 2019
- Issue No: 32
- Page Range: 82-92
- Page Count: 11
- Language: English
