Linear optimization with bipolar max-min constraints

We consider a generalization of the linear optimization problem with fuzzy relational (in)equality constraints by allowing for bipolar max-min constraints, i.e. constraints in which not only the independent variables but also their negations occur. A necessary condition to have a non-empty feasible domain is given. The feasible domain, if not empty, is algebraically characterized. A simple procedure is described to generate all maximizers of the linear optimization problem considered and is applied to various illustrative example problems.

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