Corner-point theorem
If an LPP has an optimal value, it is attained at a corner point of the feasible region. A bounded feasible region always has both a maximum and a minimum value of \(Z\).
Linear Programming
Draw each constraint line, shade the side that satisfies the inequality (test the origin), and find the common region — the feasible region. Its vertices are the corner points.
Corner-point method. (i) Find all corner points (intersections of boundary lines). (ii) Evaluate \(Z\) at each. (iii) For a bounded region the largest value is the maximum and the smallest the minimum. For the region above: \(Z=4x+3y\) takes 0, 24, 28, 24 at \((0,0),(6,0),(4,4),(0,8)\), so \(Z_{\max}=28\) at \((4,4)\).
If the region is unbounded, a candidate value \(M\) from the table is the true maximum only if the open half-plane \(px+qy>M\) has no point in common with the region (for a minimum, test \(px+qy<M\)). Otherwise the LPP has no maximum (or minimum).
If two adjacent corner points give the same optimal value, every point on the segment joining them is optimal — the LPP has infinitely many optimal solutions.
If an LPP has an optimal value, it is attained at a corner point of the feasible region. A bounded feasible region always has both a maximum and a minimum value of \(Z\).
To decide which side of \(ax+by=c\) to shade, substitute a point not on the line (usually the origin). If it satisfies the inequality, shade its side.
If \(Z\) has the same optimal value at two adjacent corners, all points on the edge joining them are optimal.
On an unbounded region the largest value in the table need not be a maximum. Draw \(px+qy>M\) and check whether it meets the region.
Maximise \(Z=60x+90y\) subject to \(x+2y\le16,\ x+y\le10,\ x,y\ge0\).
Corner points: \((0,0),(10,0),(4,6),(0,8)\). Values: 0, 600, 780, 720. The region is bounded, so \(Z_{\max}=₹780\) at \((4,6)\): make 4 mugs and 6 bowls.
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