The simplex-simulated annealing approach to continuous non-linear optimization
The simplex-simulated annealing approach to continuous non-linear optimization
复制标题
DOI：
10.1016/0098-1354(95)00221-9
复制
发表时间：
1996-09-01
影响因子：
4.3
通讯作者：
DeAzevedo, SF
中科院分区：
文献类型：
--
作者：
Cardoso, MF;Salcedo, RL;DeAzevedo, SF
提出了一种适用于非凸连续无约束和约束函数全局优化的算法。该计划是基于一个建议，由新闻和Teukolsky（计算。Phys.5（4），426，1991），其结合了非线性单纯形和模拟退火算法。一个非平衡的变体也将被提出，从而冷却时间表被强制执行，尽快获得一个改进的解决方案。后者被证明可以提供更快的执行时间，而不影响所获得的solutions.Both算法和它的非平衡变体的质量进行了测试，在文献中发表的几个严重的功能。九个这些功能的结果进行了比较，采用强大的自适应随机搜索方法和Nelder和Mead单纯形法（COMPUT。J. 7，308，1965）。所提出的方法被证明是更强大的，更有效的，在涉及克服与局部最优，起始解向量和依赖于随机数序列的困难。所获得的结果表明，在化工实践中遇到的广泛的问题的全局优化算法的充分性。(C)1996年爱思唯尔科学有限公司
An algorithm suitable for the global optimization of nonconvex continuous unconstrained and constrained functions is presented. The scheme is based on a proposal by Press and Teukolsky (Comput. Phys. 5(4), 426, 1991) that combines the non-linear simplex and simulated annealing algorithms. A non-equilibrium variant will also be presented, whereby the cooling schedule is enforced as soon as an improved solution is obtained. The latter is shown to provide faster execution times without compromising the quality of the attained solutions.Both the algorithm and its non-equilibrium variant were tested with several severe functions published in the literature. Results for nine of these functions are compared with those obtained employing a robust adaptive random search method and the Nelder and Mead simplex method (Comput. J. 7, 308, 1965). The proposed approach is shown to be more robust and more efficient in what concerns the overcoming of difficulties associated with local optima, the starting solution vector and the dependency upon the random number sequence. The results obtained reveal the adequacy of the algorithm for the global optimization of a broad range of problems encountered in chemical engineering practice. (C) 1996 Elsevier Science Ltd