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Quantum Annealing based factory layout planning

Matthias Klar, Philipp Schworm, Xiangqian Wu, Moritz Glatt, Jan C. Aurich

2022Manufacturing Letters35 citationsDOIOpen Access PDF

Abstract

Inadequately planned factory layouts can lead to higher operational costs. The planning process is time-consuming and multiple planning parameters must be considered simultaneously, leading to large solution spaces. Automated planning approaches can support the planning team in the early phases of layout planning by generating layout variants that can afterwards be further specified. Recent studies from other disciplines have shown the potential of Quantum Annealing (QA) to solve complex assignment problems within seconds. Consequently, this paper presents a first implementation of a QA-based layout planning approach and demonstrates its advantages regarding scalability, solution quality, and computing time.

Topics & Concepts

Simulated annealingScalabilityComputer scienceQuantum annealingFactory (object-oriented programming)Industrial engineeringQuantumAlgorithmQuantum computerEngineeringDatabaseProgramming languageQuantum mechanicsPhysicsAdvanced Manufacturing and Logistics OptimizationManufacturing Process and OptimizationScheduling and Optimization Algorithms
Quantum Annealing based factory layout planning | Litcius