Recent decades, the emergence of numerous novel algorithms makes it a gimmick to propose an intelligent optimization system based on metaphor, and hinders researchers from exploring the essence of search behavior in algorithms. However, it is difficult to directly discuss the search behavior of an intelligent optimization algorithm, since there are so many kinds of intelligent schemes. To address this problem, an intelligent optimization system is regarded as a simulated physical optimization system in this paper. The dynamic search behavior of such a simplified physical optimization system are investigated with quantum theory. To achieve this goal, the Schroedinger equation is employed as the dynamics equation of the optimization algorithm, which is used to describe dynamic search behaviours in the evolution process with quantum theory. Moreover, to explore the basic behaviour of the optimization system, the optimization problem is assumed to be decomposed and approximated. Correspondingly, the basic search behaviour is derived, which constitutes the basic iterative process of a simple optimization system. The basic iterative process is compared with some classical bare-bones schemes to verify the similarity of search behavior under different metaphors. The search strategies of these bare bones algorithms are analyzed through experiments.
翻译:近几十年来,许多新奇算法的出现使提出基于隐喻的智能优化系统成为了提出基于隐喻的智能优化系统,并阻碍研究人员探索算法中搜索行为的实质。 然而,由于智能优化算法有许多智能计划,因此很难直接讨论智能优化算法的搜索行为。为了解决这一问题,智能优化系统被视为本文中模拟物理优化系统。这种简化物理优化系统的动态搜索行为与量子理论一起调查。为了实现这一目标,将精子方程式用作优化算法的动态方程式,用于描述进化过程中与量子理论的动态搜索行为。此外,为了探索优化系统的基本行为,优化问题被假定是分解和近似。与此相对,基本搜索行为被推导出为简单的优化系统的基本迭代过程。基本迭代程序与一些古典的光骨头计划进行比较,以核实不同隐喻下搜索行为的相似性。这些光骨头算法的搜索策略是通过实验分析的。