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Approximation Schemes for Multi-objective Optimization with Quadratic Constraints of Fixed CP-Rank

机译:具有固定CP-Rank二次约束的多目标优化的逼近方案

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Motivated by the power allocation problem in AC (alternating current) electrical systems, we study the multi-objective (combinatorial) optimization problem where a constant number of (nonnegative) linear functions are simultaneously optimized over a given feasible set of 0-1 points defined by quadratic constraints. Such a problem is very hard to solve if no specific assumptions are made on the structure of the constraint matrices. We focus on the case when the constraint matrices are completely positive and have fixed cp-rank. We propose a polynomial-time algorithm which computes an ε-Pareto curve for the studied multi-objective problem when both the number of objectives and the number of constraints are fixed, for any constant ε > 0. This result is then applied to obtain polynomial-time approximation schemes (PTASes) for two NP-hard problems: multi-criteria power allocation and sum-of-ratios optimization.
机译:受交流(交流)电气系统中的功率分配问题的影响,我们研究了多目标(组合)优化问题,其中在定义的0-1点的给定可行集合上同时优化了恒定数量(负)线性函数受二次约束。如果不对约束矩阵的结构进行特定假设,则很难解决该问题。我们关注约束矩阵完全为正且具有固定cp-rank的情况。我们提出了一种多项式时间算法,当目标数和约束数均固定时(对于任何常数ε> 0),该算法可为所研究的多目标问题计算一条ε-帕累托曲线。然后将该结果应用于获得多项式两个NP难题的时间近似方案(PTAS):多准则功率分配和比率总和优化。

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