Smart Bacterial Foraging considering Evolutionary and Heuristic Strategies for Optimization practices

In this paper, a smart bacterial foraging optimization method considering evolutionary and heuristic strategies (SBFEH) is developed, which enjoys an individual intelligence (how to achieve a goal) and social intelligence (how to collaborate or compete with others for resources). The algorithm inspires some evolutionary and physiological heuristic strategies, which provide a higher performance in terms of efficiency and effectiveness. In other words, the exploration and exploitation of the proposed algorithm are improved. The proposed algorithm is applied on different benchmark functions including some CEC05/13 functions and two well-known engineering design optimization problems, the results obtained show that the SBFEHS algorithm is either more accurate and scalable or competitive than those algorithms available in the literature. In addition, a practical water management problem-based optimization is deal with the proposed algorithm in comparison with other state of art solutions.