0-1非线性规划问题改进的教与学优化算法  

Improved Teaching-learning-based Optimization Algorithm for Solving Zero-one Nonlinear Programming Problems

作　　者：张林[1] 李会荣[1] ZHANG Lin;LI Huirong(Department of Mathematics and Computer Science,Shangluo University,Shangluo 726000)

机构地区：[1]商洛学院数学与计算机应用学院,商洛726000

出　　处：《计算机与数字工程》2017年第5期835-838,共4页Computer & Digital Engineering

摘　　要：将0-1非线性规划问题转化为约束优化问题,采用动态双目标的约束处理方法,对教与学优化算法的迭代方程进行改进,提出了一种求解0-1非线性规划问题的改进教与学优化算法。数值实验表明,新算法具有较快的收敛速度和较好的全局寻优能力,显示了算法的有效性和通用性。The zero-one nonlinear programming problems is converted constrained optimization problems,an improved teaching-learning-based optimization(ITLBO)for solving the zero-one nonlinear programming is proposed using dynamic bi-objection constraint-handling method and modifying the iterative equation of TLBO algorithm.Simulation results show that ITLBO is effectiveness in terms of convergence speed and global optimization ability.

关 键 词：0-1非线性规划 约束优化 教与学优化算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]