EFFICIENT INTERACTIVE METHODS FOR A CLASS OF MULTIATTRIBUTE SHORTEST-PATH PROBLEMS

Given an acyclic network and a preference-order relation on paths, when and how can Bellman's principle of optimality be combined with interactive programming to efficiently locate an optimal path? We show that if preferences are defined via a collection of attributes, then, under common conditions, the principle of optimality is valid if and only if the preferences can be represented by a linear (value) function over the attributes. Consequently, an interactive programming method is suggested which assesses the value function while using the principle of optimality to efficiently search for an optimal path.