Satisfying solutions for a possibilistic linear program

A branch and bound scheme is described for tackling a linear program under discrete possibilistic data. We grapple also with the continuous case via recent results on inexact and semiinfinite programming. It is shown that solutions yielded by these techniques are satisfying, i.e. possibly and/or necessarily feasible, and optimal to a great extent. Finally, approaches reported here and elsewhere are appraised in the light of their decision-making philosophies, and some directions for further developments indicated.