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Faster integer-feasibility in mixed-integer linear programs by branching to force change

机译:通过分支强制变化,在混合整数线性程序中更快地实现整数可行性

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Branching in mixed-integer (or integer) linear programming requires choosing both the branching variable and the branching direction. This paper develops a number of new methods for making those two decisions either independently or together with the goal of reaching the first integer-feasible solution quickly. These new methods are based on estimating the probability of satisfying a constraint at the child node given a variable/direction pair. The surprising result is that the first integer-feasible solution is usually found much more quickly when the variable/direction pair with the smallest probability of satisfying the constraint is chosen. This is because this selection forces change in many candidate variables simultaneously, leading to an integer-feasible solution sooner. Extensive empirical results are given.
机译:混合整数(或整数)线性编程中的分支需要选择分支变量和分支方向。本文开发了许多新方法,可以独立地或一起制定这两个决策,以期快速达到第一个整数可行解。这些新方法基于估计给定变量/方向对的子节点满足约束的概率。令人惊讶的结果是,当选择变量/方向对满足约束的可能性最小时,通常会更快地找到第一个整数可行解。这是因为此选择力会同时在许多候选变量中发生变化,从而更快地得出整数可行解。给出了广泛的经验结果。

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