The ‘Light Beam Search’ approach – an overview of methodology applications

Abstract

The paper gives a general overview of the Light Beam Search (LBS) methodology and applications. LBS enables an interactive analysis of multiple-objective decision problems due to presentation of samples of a large set of non-dominated points, to the decision maker (DM) in each iteration. A local preference model in the form of an outranking relation is used to define the neighborhood of a current non-dominated point the sample comes from. The first current point is obtained by projection of an aspiration point onto the non-dominated set in the direction of a reservation point. The DM can control the search by either modifying the aspiration and reservation points, or by shifting the current point to a selected better point from its neighborhood. The paper describes applications of the approach to several real life problems and discusses observations made while working on these problems. The LBS approach is compared to other existing methods and the class of problems suitable to this methodology is defined.