一类具约束选址模型的组合算法

针对一般具闭凸集约束的单址选址模型,提出具全局收敛性的组合算法．算法在迭代中先采用信赖域技巧,当出现“内循环”时,则改用不做线搜索的梯度法．该算法既具有信赖域算法的优越性,又避免了出现“内循环”时速成的隐迭代．同时,该算法通常不需进行线搜索,较之其它组合算法更加简捷实用．

Combining Algorithm for a Kind of Constrained Location Model

For very general single location on a closed convex domain,propose a combining algorithm which has global convergence.The aogorithm uses the TR technique first,but it takes the gradient method which doesn't use the linear search instead of resolving the subproblem when the trial step is not successful.The algorithm overcomes the drawback that the original gradient methods are ineffective when an iterative point is an extreme point,and may not usually make a linear search.The algorithm has good quality as TR algorithm,but it avoid the "inner cycle" which may arise in TR algorithm.