Intelligent Exploration of Solution Spaces Exemplified by Industrial Reconfiguration Management
This addresses the challenge of efficient solution space exploration for decision-makers in complex industrial settings, but it appears incremental as it builds on existing subdivision concepts.
The paper tackles the problem of exploring solution spaces in complex decision-making environments where brute-force methods are infeasible, proposing a methodology that combines vertical and horizontal subdivisions of exploration tasks, with a specific example from industrial reconfiguration management.
Many decision-making approaches rely on the exploration of solution spaces with regards to specified criteria. However, in complex environments, brute-force exploration strategies are usually not feasible. As an alternative, we propose the combination of an exploration task's vertical sub-division into layers representing different sequentially interdependent sub-problems of the paramount problem and a horizontal sub-division into self-sustained solution sub-spaces. In this paper, we present a universal methodology for the intelligent exploration of solution spaces and derive a use-case specific example from the field of reconfiguration management in industry 4.0.