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基于学习的积极和消极现象,提出一种新的启发式智能优化算法:学习搜索算法(LSA).该算法设计了两种学习模式,一是积极模式,充分发挥当前最优学生的引导作用,使所有学生进行积极地学习,不断提升学识水平;二是消极模式,有效地吸收最差学生所具有的优点,增强学习的全面性.利用这两种模式的结合,有效地均衡学习搜索算法的全局搜索能力和局部搜索能力.为了验证学习搜索算法的有效性,对几个经典基准函数进行了测试,结果表明,算法在整体上优于其他几个有发展潜力的启发式算法,具有更好的优化潜力.
Based on the positive and negative phenomena of learning, this paper proposes a new heuristic intelligent optimization algorithm: learning search algorithm (LSA) .The algorithm designs two learning modes: one is a positive model, giving full play to the guiding role of the current best student, So that all students to actively learn and improve their level of knowledge; the second is a negative model, effectively absorbing the advantages of the worst students, and enhance the learning comprehensiveness of the use of these two models combined to effectively balance the learning search algorithm Global search ability and local search ability.In order to verify the effectiveness of learning search algorithm, several classical benchmark functions have been tested and the results show that the algorithm is better than several other heuristic algorithms with better development potential, which is better The optimization potential.