| John Chinneck. Finding Minimal Infeasible Sets of Constraints in Infeasible Mathematical Programs. Technical Report SCE-93-01, Department of Systems and Computer Engineering, Carleton University, Ottawa, 1993. |
....of each system; their negations are summarised alongside their advantages in a later section which lists the characteristics of the ideal system. ffl In linear programming, Chinneck and Dravnieks have done some work on what they term IIS s (infeasible systems of linear equations and inequalities) [14, 15]. They relax each inequality i by adding a distinct new variable ffl i to it, and replace the original optimisation function with one which minimises the sum of the ffl s. Any non zero ffl in the answer indicates one member of the minimal infeasible subset. If that ffl is then removed and the ....
John Chinneck. Finding Minimal Infeasible Sets of Constraints in Infeasible Mathematical Programs. Technical Report SCE-93-01, Department of Systems and Computer Engineering, Carleton University, Ottawa, 1993.
....will provide a localization of the modeling error inconsistency. Thus, this approach provides a framework with which not only to isolate the infeasibility, but also to diagnose the infeasibility. To date, this approach had only been explored in the theoretical sense. Recently, Chinneck (e.g. 13] [10], 11] has developed a set of software tools to bring I IS isolation into practical use in LP infeasibility analysis. The goal of these algorithms is to identify a small cardinality I ISs, the idea being that the smaller the constraint set the infeasibility is isolated to the easier the actual ....
Chinneck J., Finding Minimal Infeasible Sets of Constraints in Infeasible Mathematical Programs, Technical Report SCE-93-01, Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada, 1993.
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