This may be a silly question, but integer linear programming seems to be about maximizing some quantity relative to constraints given by a matrix equality (or inequality), where everything is happening over the integers. How does this relate to finding integer solutions to a matrix equation?
for example you could maximize vx with constraint Ax <= b for a random vector v, and do the same for Ax >= b. If a solution exists, it should be found this way. I find myself wanting to do something similar: find *all* solutions to Ax = b, where A, x, and b have non-negative integer entries. I'm trying to figure out if the various responses here will help me. In the situation of interest to me, I know that there are only finitely many solutions, and I know one solution. By "rotating" the vector v, you will find solutions on the convex hull of the solution set with the (very naive) algorithm above. Paul Zimmermann --~--~---------~--~----~------------~-------~--~----~ To post to this group, send email to sage-support@googlegroups.com To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/sage-support URLs: http://www.sagemath.org -~----------~----~----~----~------~----~------~--~---
