论文标题
Pamilo：多目标混合整数线性优化及以后的求解器
PaMILO: A Solver for Multi-Objective Mixed Integer Linear Optimization and Beyond
论文作者
论文摘要
在多目标优化中，需要优化几种潜在的目标功能。我们寻找一组所谓的非主导解决方案，而不是一种最佳解决方案。 一个重要的子集是一组非主导的极端点。一般而言，发现这是一个计算困难的问题。尽管存在类似问题的求解器，但多目标混合整数线性程序（MOMILPS）或多目标混合整数四边形二次二次程序（MOMIQCCPS）都不知道。我们提出了帕米洛（Pamilo），这是第一个找到非主导妈妈和莫姆克格斯（Momiqcqps）极端点的求解器。它可以在github.com/fritzbo/pamilo下的GitHub上找到。 Pamilo提供了易于使用的接口，并在C ++ 17中实现。它解决了使用CPLEX或GUROBI的子问题的发生。 帕米洛（Pamilo）适应了多目标线性编程（MOLP）的双苯后算法。正如以前仅针对Molps定义的那样，我们描述了如何适应妈妈，Momiqcqps甚至更多的问题类别。
In multi-objective optimization, several potentially conflicting objective functions need to be optimized. Instead of one optimal solution, we look for the set of so called non-dominated solutions. An important subset is the set of non-dominated extreme points. Finding it is a computationally hard problem in general. While solvers for similar problems exist, there are none known for multi-objective mixed integer linear programs (MOMILPs) or multi-objective mixed integer quadratically constrained quadratic programs (MOMIQCQPs). We present PaMILO, the first solver for finding non-dominated extreme points of MOMILPs and MOMIQCQPs. It can be found on github under github.com/FritzBo/PaMILO. PaMILO provides an easy-to-use interface and is implemented in C++17. It solves occurring subproblems employing either CPLEX or Gurobi. PaMILO adapts the Dual-Benson algorithm for multi-objective linear programming (MOLP). As it was previously only defined for MOLPs, we describe how it can be adapted for MOMILPs, MOMIQCQPs and even more problem classes in the future.
