A LP Relaxation based Matheuristic for Multi-objective Integer Programming

Duleabom An, Sophie N. Parragh, Markus Sinnl, Fabien Tricoire
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引用次数: 2

Abstract

Motivated by their success in the single-objective domain, we propose a very simple linear programming-based matheuristic for tri-objective binary integer programming. To tackle the problem, we obtain lower bound sets by means of the vector linear programming solver Bensolve. Then, simple heuristic approaches, such as rounding and path relinking, are applied to this lower bound set to obtain high-quality approximations of the optimal set of trade-off solutions. The proposed algorithm is compared to a recently suggested algorithm which is, to the best of our knowledge, the only existing matheuristic method for tri-objective integer programming. Computational experiments show that our method produces a better approximation of the true Pareto front using significantly less time than the benchmark method on standard benchmark instances for the three-objective knapsack problem.
基于LP松弛的多目标整数规划数学
由于他们在单目标领域的成功,我们提出了一个非常简单的基于线性规划的三目标二进制整数规划数学。为了解决这个问题,我们利用向量线性规划求解器Bensolve得到下界集。然后,将简单的启发式方法(如舍入和路径重链接)应用于该下界集,以获得最优权衡解集的高质量近似值。该算法与最近提出的一种算法进行了比较,据我们所知,该算法是三目标整数规划的唯一现有数学方法。计算实验表明,在三目标背包问题的标准基准实例上,我们的方法比基准方法用更少的时间产生了更好的逼近真实Pareto前的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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