Krill herd (KH) algorithm for portfolio optimization
نویسنده
چکیده
This paper presents novel krill herd (KH) nature-inspired metaheuristics for solving portfolio optimization task. Krill herd algorithm mimics the herding behavior of krill individuals. The objective function for the krill movement is defined by the minimum distances of each individual krill from food and from higher density of the herd. Constrained portfolio optimization problem extends the classical mean-variance portfolio problem by adding constraints to the basic problem definition. For optimizing constraint portfolio problem, traditional optimization techniques do not obtain satisfying results, and the usage of metaheuristics approach is necessary. Experimental results show that the krill herd algorithm is a promising technique for tackling portfolio optimization problems. Key–Words: portfolio optimization problem, metaheuristic optimization, swarm intelligence, krill herd (KH) algorithm, nature-inspired algorithms
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