Objective Function Designing Led by User Preferences Acquisition
This work addresses the tedious process of objective function design for users in optimization tasks, though it appears incremental as it builds on existing interactive approaches.
The paper tackles the challenge of designing objective functions that accurately reflect user needs in optimization problems by introducing an interactive method based on man-machine dialogue and solution comparisons. It demonstrates promising results in an experiment on cartographic generalization.
Many real world problems can be defined as optimisation problems in which the aim is to maximise an objective function. The quality of obtained solution is directly linked to the pertinence of the used objective function. However, designing such function, which has to translate the user needs, is usually fastidious. In this paper, a method to help user objective functions designing is proposed. Our approach, which is highly interactive, is based on man machine dialogue and more particularly on the comparison of problem instance solutions by the user. We propose an experiment in the domain of cartographic generalisation that shows promising results.