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Robust and Constrained Portfolio Optimization using Multiobjective Evolutionary Algorithms

机译:使用多目标进化算法的鲁棒约束证券优化

摘要

Optimization plays an important role in many areas of science, management,economics and engineering. Many techniques in mathematics and operation research are available to solve such problems. However these techniques have many shortcomings to provide fast and accurate solution particularly when the optimization problem involves many variables and constraints. Investment portfolio optimization is one such important but complex problem in computational finance which needs effective and efficient solutions. In this problem each available asset is judiciously selected in such a way that the total profit is maximized while simultaneously minimizing the total risk. The literature survey reveals that due to non availability of suitable multi objective optimization tools, this problem is mostly being solved by viewing it as a single objective optimization problem.
机译:优化在科学,管理,经济学和工程学的许多领域都起着重要作用。数学和运筹学中的许多技术可用于解决此类问题。但是,这些技术具有许多缺点,无法提供快速而准确的解决方案,尤其是当优化问题涉及许多变量和约束时。投资组合优化是计算金融中如此重要但复杂的问题之一,需要有效的解决方案。在这个问题中,以使总利润最大化而同时使总风险最小化的方式来明智地选择每种可用资产。文献调查表明,由于没有合适的多目标优化工具,该问题通常通过将其视为单个目标优化问题来解决。

著录项

  • 作者

    Mishra Sudhansu Kumar;

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  • 年度 2012
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