On the Bottleneck Structure of Positive Linear Programming
Jordi Ros-Giralt, Harper Langston, Aditya Gudibanda, Richard Lethin
Publication Source: 2019 SIAM Workshop on Network Science
Positive linear programming (PLP), also known as packing and covering linear programs, is an important class of problems frequently found in fields such as network science, operations research, or economics. In this work we demonstrate that all PLP problems can be represented using a network structure, revealing new key insights that lead to new polynomial-time algorithms.