Take the dual vector . Its column constraints have values , exceeding or equaling ; its entries are positive. Thus it is dual feasible. The first two constraints are equalities while the last two have strictly positive slack, suggesting . Solve the two primal equalities to get , , both positive.
The resulting feasible objectives agree:
Weak duality proves optimality. Strict dual slack in columns three and four and positive dual entries force the two primal equalities, proving primal uniqueness; positive first two primal coordinates force the two independent dual equalities, proving dual uniqueness.

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