ABSTRACT

The optimization problems are becoming more complicated, requiring new and efficient optimization techniques to solve them. Many bio-inspired meta-heuristic algorithms have emerged in the last decade to solve these complex problems as most of these algorithms may be trapped into local optima and could not effectively solve all types of optimization problems. Hence, researchers are still trying to develop new and better optimization algorithms. This paper introduces a novel biologically-based optimization algorithm called circulatory system-based optimization (CSBO). CSBO is modeled based on the function of the body’s blood vessels with two distinctive circuits, i.e. pulmonary and systemic circuits. The proposed CSBO algorithm is tested on a wide variety of complex functions of the real world and validated with the standard meta-heuristic algorithms. The results indicate that the CSBO algorithm successfully achieves the optimal solutions and avoids local optima. Note that the source code of the CSBO algorithm is publicly available at http://www.optim-app.com/projects/csbo.

摘要

优化问题变得越来越复杂，需要新的高效优化技术来解决它们。在过去的十年中出现了许多受生物启发的元启发式算法来解决这些复杂的问题，因为这些算法中的大多数可能会陷入局部最优并且无法有效地解决所有类型的优化问题。因此，研究人员仍在尝试开发新的更好的优化算法。本文介绍了一种新的基于生物学的优化算法，称为基于循环系统的优化 (CSBO)。CSBO 是根据人体血管的功能建模的，具有两个独特的回路，即肺回路和全身回路。所提出的 CSBO 算法在现实世界的各种复杂函数上进行了测试，并使用标准元启发式算法进行了验证。结果表明，CSBO算法成功地达到了最优解，避免了局部最优。请注意，CSBO 算法的源代码可在 http://www.optim-app.com/projects/csbo 公开获得。