中文说明：在日益复杂的现实问题促使计算机科学家寻找efficientproblem解决方法。基于进化计算和群intelligenceare自然启发的解决方案技术的优秀实例的启发式。受社会蜘蛛的启发，我们提出了一种新的社会蜘蛛算法来解决全局优化问题。该算法主要是基于社会性蜘蛛的捕食策略，利用振动对蜘蛛网来确定猎物的位置。不同于先前提出的群智能算法，引入了一个新的社会动物的觅食策略模型求解优化问题。此外，我们提出的算法，我们performpreliminary参数敏感性分析，对选择的参数值的制定原则。社会的蜘蛛算法是由一系列的广泛应用benchmarkfunctions评价，和我们提出的算法具有优越的性能，与其他国家相比的artmetaheuristics
English Description：
tThe growing complexity of real-world problems has motivated computer scientists to search for efficientproblem-solving methods. Metaheuristics based on evolutionary computation and swarm intelligenceare outstanding examples of nature-inspired solution techniques. Inspired by the social spiders, we pro-pose a novel social spider algorithm to solve global optimization problems. This algorithm is mainlybased on the foraging strategy of social spiders, utilizing the vibrations on the spider web to determinethe positions of preys. Different from the previously proposed swarm intelligence algorithms, we intro-duce a new social animal foraging strategy model to solve optimization problems. In addition, we performpreliminary parameter sensitivity analysis for our proposed algorithm, developing guidelines for choos-ing the parameter values. The social spider algorithm is evaluated by a series of widely used benchmarkfunctions, and our proposed algorithm has superior performance compared with o