Collective Decision-Making by Bee Colonies as Model for Optimization - the OptBees Algorithm

This paper presents OptBees, a new bee-inspired algorithm for solving continuous optimization problems. Two key mechanisms for OptBees are introduced: 1) a local search step; and 2) a process of dynamic variation of the number of active bees that helps the algorithm to regulate the computational effort spent in the search and to achieve improved results. The performance of the algorithm was evaluated, in terms of global search, in all twenty-five minimization problems proposed for the Optimization Competition of Real Parameters of the CEC 2005 Special Session on Real-Parameter Optimization, held in the 2005 IEEE Congress on Evolutionary Computation (CEC). The results obtained show that OptBees is a fairly powerful search approach, presenting a superior performance to many of the competitors and other more recent algorithms also evaluated in these problems, including other bee-inspired approaches.