摘要
TS算法属于现代优化算法 ,是局部领域搜索法的推广 ,常用于求解组合优化问题 .利用TS法搜索过程的有向性和能够跳离局部最优解的特点 ,对其进行了改造 ,以适应求解连续变量化工优化问题 .首先 ,根据化工优化问题变量的特性 ,提出了一种简便的邻域映射方案 ,并改进了迭代过程中自适应因子的下降函数 ;进一步分析对比了禁忌步数、自适应因子和初始解等参数对于优化结果的影响 然后通过算例和换热网络优化问题的求解 ,表明改造后的TS法在求解连续变量化工优化问题中的有效性 ,及其在化工优化领域的发展价值 .
The tabu search (TS) method is one of the modern optimization algorithms developed from local search. It is generally used in combinatorial optimization problem. The TS method performs a guided search which enables it to escape from local optima. The improved TS method has introduced to search the global optimal solution to optimization problems with continuous variables. First, according to the property of the continuous variable problem, an easy function of producing adjacent state was proposed and the function of the declining search scale was improved. The effects of tabu space, search scale and initial solution on the optimal calculation were analyzed as well. Then, the example of solving heat exchangers network problem showed the efficiency of the improved tabu search method applied to continuous variables optimization problems in chemical engineering.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2004年第10期1665-1668,共4页
CIESC Journal
关键词
禁忌算法
连续变量
化工优化
换热网络
Algorithms
Calculations
Chemical engineering
Chemical variables control
Heat exchangers
