Dealing with User’s Preferences in Mixed-Initiative Systems for Linear Optimization

Mixed-Initiative Systems (MIS) are hybrid decision systems where collaboration is possible between humans and machines. However, current systems sometimes override user preferences when provided with new ones. We studied linear optimization problems, where the decision maker is specifying preferences for variable values through an iterative process. We proposed a goal programming framework to deal with hierarchies of preferences. Two reoptimization algorithms were evaluated: sequential simplex and lexicographic simplex. Compared with the sequential simplex, the lexicographic simplex algorithm demonstrated greater speed and numerical stability. Keywords—mixed-initiative systems, MIS, optimization, reoptimization, preference, real-time, performance, man-machine interaction, user experience, UX.