A Dual-Strategy Contest Harmony Search Algorithm Based on Population State for the System Reliability-Redundancy Allocation Problems

At present, many improved algorithms have effectively improved the ability to converge to the optimal value. However, there are still difficulties: how to effectively balance the deep development ability of the algorithm in a small range and the extensive exploration ability in the global search field in the iterative process. For this reason, this topic first proposes a population state evaluation indicator, which continuously detects the state and diversity of the population with iteration. On this basis, the dual-strategy competition mechanism is adopted. Through the population state evaluation index, the strategy can select a strategy that is more conducive to rapid convergence according to the changes of the population during the iteration process. Through the advantage competition of the two strategies, the development ability of the algorithm has been steadily and persistently improved. However, there is still the risk of falling into the local optimal dilemma. Therefore, the change of population diversity is considered in the evaluation index of population status in this study. In order to further increase the activity of the global search range, the computational individuals used in the proposed environmental assessment index of population diversity are randomly selected. In general, in the greedy comparison of the two strategies, this study still ensures the consideration and influence of diversity, and effectively balances the ability of algorithm exploration and development.