A reactive greedy randomized adaptive search procedure for a mixed integer portfolio optimization problem

摘要

Purpose - The purpose of this paper is to present a procedure for finding the efficient frontier, i.e. arnnon-decreasing curve representing the set of Pareto-optimal or non-dominated portfolios, when thernstandard Markowitz' classical mean-variance model is enriched with additional constraints.rnDesign/methodology/approach - The mean-variance portfolio optimization model is extended torninclude integer constraints that limit a portfolio to have a specified number of assets, and to imposernlimits on the proportion of the portfolio held in a given asset. Optimization-based procedures run intorndifficulties in this framework and this motivates the investigation of heuristic algorithms to findrnacceptable solutions.rnFindings - The problem is solved by a greedy randomized adaptive search procedure (GRASP),rnenhanced by a learning mechanism and a bias function for determining the next element to bernintroduced in the solution.rnOriginality/value - This is believed to be the first time, a GRASP for finding the efficient frontierrnfor this class of portfolio selection problems is used.