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A LINEAR FRACTIONAL OPTIMIZATION OVER AN INTEGER EFFICIENT SET

机译:整数有效集上的线性分数最优化

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Mathematical optimization problems with a goal function, have many applications in various fields like financial sectors, management sciences and economic applications. Therefore, it is very important to have a powerful tool to solve such problems when the main criterion is not linear, particularly fractional, a ratio of two affine functions. In this paper, we propose an exact algorithm for optimizing a linear fractional function over the efficient set of a Multiple Objective Integer Linear Programming (MOILP) problem without having to enumerate all the efficient solutions. We iteratively add some constraints, that eliminate the undesirable (not interested) points and reduce, progressively, the admissible region. At each iteration, the solution is being evaluated at the reduced gradient cost vector and a new direction that improves the objective function is then defined. The algorithm was coded in MATLAB environment and tested over different instances randomly generated.
机译:具有目标函数的数学优化问题在金融领域,管理科学和经济应用等各个领域都有许多应用。因此,当主要判据不是线性的,尤其是分数的两个仿射函数之比不是线性的时候,拥有一个强大的工具来解决这些问题非常重要。在本文中,我们提出了一种精确算法,用于在多目标整数线性规划(MOILP)问题的有效集上优化线性分数函数,而不必列举所有有效的解决方案。我们反复添加一些约束,以消除不想要的(不感兴趣的)点并逐渐减小可允许的区域。在每次迭代中,都以降低的梯度成本向量评估解决方案,然后定义改善目标函数的新方向。该算法在MATLAB环境中进行了编码,并在随机生成的不同实例上进行了测试。

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