Constraint-Based Optimization with the Minimax Decision Criterion

Abstract. In many situations, a set of hard constraints encodes the feasible configurations of some system or product over which users have preferences. We consider the problem of computing a best feasible solution when the user’s utilities are partially known. Assuming bounds on utilities, efficient mixed integer linear programs are devised to compute the solution with minimax regret while exploiting generalized additive structure in a user’s utility function.

• Type: Conference
• Year: 2003
• Where: CP
• Authors: Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans
• Keywords: CP 2003, Feasible Configurations, Mixed Integer Linear, Programming Languages, User’s Utility Function