Using Elitist Particle Swarm Optimization to Facilitate Real Estate Portfolio Based on Information Entropy

The real estate industry has been the pillar industry of national economic. And the high returns and high risks would coexist in this industry. First, this paper established the real estate portfolio model based on information entropy, with the smallest risk as the greatest benefits. In addition, this paper developed a new algorithm to find the optimal real estate portfolio to achieve the smallest risk as the greatest benefits. And the proposed algorithm modified a population-based search procedure, particle swarm optimization, by adopting an elite archiving scheme to store nondominated solutions and by aptly using members of the archive to direct further search. Moreover, the termination of the proposed algorithm was set to that no new members have entered into the elite archive. In addition, through a practical case, the proposed algorithm is shown effective and efficient in real estate portfolio.