Reduced search space mechanism for solving constrained optimization problems. (October 2017) - Sallam, Karam M.; Sarker, Ruhul A.; Essam, Daryl L.
Abstract: Over the last few decades, a considerable number of evolutionary algorithms (EAs) have been proposed for solving constrained optimization problems (COPs). As for most of these problems, the optimal solution exists on the boundary of the feasible space, we aim to focus the search process around the boundary. In this paper a new concept, called reduced search space (R2S), is introduced. In the process, we first identify active constraints, based on the current solutions, and then define R2S around those constraint's boundaries. However, the search may be conducted either in the entire R2S or in some portions of it. To judge the impact of this concept, we have incorporated it with a number of state-of-the-art algorithms, and we have comprehensively tested it on three sets of benchmark test functions, namely, 24 test functions taken from IEEE CEC2006, 18 test functions with 10 D and 30 D taken from IEEE CEC2010 and 10 test functions taken from IEEE CEC2011. The results show that our proposed mechanism significantly improves the performances of state-of-the-art algorithms. Highlights: An active constraint determination mechanism is proposed. A reduced search space (R2S) is proposed to solve COPs. Two COPs benchmark-sets were considered for comparison. Ten real-world COPs had been solved. Experiments showed that the proposed method outperforms state-of-the-art algorithms.