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How long should offspring lifespan be in order to obtain a proper exploration?

机译:为了获得适当的探索,后代的寿命应该多长?

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The time an offspring should live and remain into the population in order to evolve and mature is a crucial factor of the performance of population-based algorithms both in the search for global optima, and in escaping from the local optima. Offsprings lifespan influences a correct exploration of the search space, and a fruitful exploiting of the knowledge learned. In this research work we present an experimental study on an immunological-inspired heuristic, called OPT-IA, with the aim to understand how long must the lifespan of each clone be to properly explore the solution space. Eleven different types of age assignment have been considered and studied, for an overall of 924 experiments, with the main goal to determine the best one, as well as an efficiency ranking among all the age assignments. This research work represents a first step towards the verification if the top 4 age assignments in the obtained ranking are still valid and suitable on other discrete and continuous domains, i.e. they continue to be the top 4 even if in different order.
机译:后代生存和留在种群中以发展和成熟的时间是基于种群的算法在寻找全局最优值和逃避局部最优值方面的性能的关键因素。后代的寿命会影响对搜索空间的正确探索,以及对所学知识的丰富利用。在这项研究工作中,我们提出了一种以免疫学启发式启发式实验方法OPT-IA的实验研究,目的是了解每个克隆的寿命必须多长时间才能正确探索溶液空间。已经考虑并研究了11种不同类型的年龄分配,总共进行了924个实验,其主要目标是确定最佳年龄分配以及所有年龄分配中的效率排名。这项研究工作代表着朝着验证迈出的第一步,即所获得排名中的前4个年龄分配是否仍然有效并且适用于其他离散和连续领域,即即使按不同的顺序,它们仍然是前4个年龄分配。

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