论文部分内容阅读
约束优化问题是工程应用领域经常出现的一类数学规划问题,近年来,约束优化问题求解已成为进化计算研究的一个重要方向.而一系列新型的进化计算方法 ,如人工神经网络、模拟退火、遗传算法、进化规划、进化策略、粒子群、人工鱼群等获得了极其迅速的发展和广泛的应用.本文提出了一种基于人工萤火虫群优化算法求解约束优化问题的新方法.该方法在求解约束优化问题的过程中,不断地寻找更优可行解,逐渐达到搜索全局最优解.通过标准测试函数和工程实例仿真表明,该方法能很好的求解约束优化问题,精度高、适应性强,在工程实际中有较大的应用价值.
Constrained optimization problems are often a kind of mathematical programming problems in engineering application field. In recent years, the problem of constrained optimization problems has become an important direction of evolutionary computation research. A series of new evolutionary computation methods, such as artificial neural networks, simulated annealing, Genetic Algorithm, Evolutionary Programming, Evolutionary Strategy, Particle Swarm, Artificial Fish Swarm and so on have been developed extremely rapidly and widely used.This paper presents a new method based on Artificial Firefly Swarm Optimization algorithm for solving constrained optimization problems.This method, In the process of constrained optimization problem, we always look for a better feasible solution and gradually reach the global optimal solution.It is proved by the standard test function and engineering example that this method can well solve the constrained optimization problem with high precision and strong adaptability , In the actual project has greater application value.