Intelligent Exploration of Solution Spaces Exemplified by Industrial Reconfiguration Management

TL;DR

This paper introduces a universal methodology for intelligently exploring complex solution spaces by dividing problems into interdependent layers and sub-spaces, demonstrated through an industrial reconfiguration management case in Industry 4.0.

Contribution

It presents a novel approach to explore solution spaces efficiently by hierarchical and sub-space division, applicable to complex industrial decision-making problems.

Findings

Effective hierarchical exploration of solution spaces.

Application to industrial reconfiguration management.

Potential for improved decision-making efficiency.

Abstract

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.