Stepsize Control on the Modified Bacterial Foraging Algorithm for Constrained Numerical Optimization

The stepsize value is one of the most sensitive parameters in the bacterial foraging optimization algorithm when solving constrained numerical optimization problems. In this paper, four stepsize control mechanisms are proposed and analyzed in the modified bacterial foraging optimization algorithm. The first one is based on a random value which remains fixed during the search, the second one generates a random value per cycle, the third one is based on a nonlinear decreasing function and the last one is an adaptive approach. Seven experiments are proposed to evaluate the abilities of each mechanism to: (1) obtain competitive final results, (2) find feasible solutions, (3) find the feasible global optimum, (4) promote successful swims, and (5) decrease the constraint violation. A comparison against two state-of-theart algorithms is considered to evaluate the performance of the most competitive control mechanism. A well-known set of constrained numerical optimization problems is used in the experiments as well as six performance measures. The results obtained show that the control mechanism based on the nonlinear decreasing function is the most competitive and provides the ability to generate better solutions late in the search.