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Minimal infeasible constraint sets in convex integer programs

机译:凸整数程序中的最小不可行约束集

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In this paper we investigate certain aspects of infeasibility in convex integer programs, where the constraint functions are defined either as a composition of a convex increasing function with a convex integer valued function of n variables or the sum of similar functions. In particular we are concerned with the problem of an upper bound for the minimal cardinality of the irreducible infeasible subset of constraints defining the model. We prove that for the considered class of functions, every infeasible system of inequality constraints in the convex integer program contains an inconsistent subsystem of cardinality not greater than 2~n, this way generalizing the well known theorem of Scarf and Bell for linear systems. The latter result allows us to demonstrate that if the considered convex integer problem is bounded below, then there exists a subset of at most 2~n - 1 constraints in the system, such that the minimum of the objective function subject to the inequalities in the reduced subsystem, equals to the minimum of the objective function over the entire system of constraints.
机译:在本文中,我们研究了凸整数程序中不可行的某些方面,其中约束函数定义为由n个变量的凸整数值函数或相似函数之和组成的凸递增函数的组合。特别地,我们关注的是定义模型的不可约的不可行约束子集的最小基数上限的问题。我们证明,对于所考虑的函数类别,凸整数程序中的每个不可行的不等式约束系统都包含一个不大于2〜n的不一致基数子系统,从而将Scarf和Bell的定理推广为线性系统。后一个结果使我们能够证明,如果所考虑的凸整数问题在以下范围内,则系统中最多存在2〜n-1个约束的子集,使得目标函数的最小值服从于不等式中的不等式。简化的子系统,等于整个约束系统中目标函数的最小值。

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