Interactive Reference Point-Based Guided Local Search for the
  Bi-objective Inventory Routing Problem
  Eliciting preferences of a decision maker is a key factor to successfully
combine search and decision making in an interactive method. Therefore, the
progressively integration and simulation of the decision maker is a main
concern in an application. We contribute in this direction by proposing an
interactive method based on a reference point-based guided local search to the
bi-objective Inventory Routing Problem. A local search metaheuristic, working
on the delivery intervals, and the Clarke & Wright savings heuristic is
employed for the subsequently obtained Vehicle Routing Problem. To elicit
preferences, the decision maker selects a reference point to guide the search
in interesting subregions. Additionally, the reference point is used as a
reservation point to discard solutions outside the cone, introduced as a
convergence criterion. Computational results of the reference point-based
guided local search are reported and analyzed on benchmark data in order to
show the applicability of the approach.
