【摘要】 <正>1引言科学和工程领域中的许多优化问题最终可以归结为求解一个带有约束条件的整数规划问题。其形式为:式中I表示整数集,x=（x₁,…,x_n）^T,A_i（i∈{1,…,n}）为有限整数集。遗传算法作为一种优化技术,是一种近似算法,一般不能保证一定能得到优化问题的精确解。为了提高算法的精确度,人们提出许多改进算法,例如遗传模拟退火算法、"优胜劣汰"遗传算法、基于最优保存和自适应的遗传算法等。更多还原

【Abstract】 In this paper a hybrid genetic algorithm for integer programming, which integrates both a genetic algorithm and a simulated annealing algorithm by a new method to avoid large drop of the algorithm’s efficiency is proposed.A new"nature select"rule is added into the algorithm to ensure that it converges to optimal solution with probability 1.And also individuals more than one are generated by a pair of parents to improve individuals’ diversity and algorithm’s local search ability.The algorithm’s convergence is proved using the theory of Markov chain,and effectiveness is examined by several numerical experiments.更多还原