State-of-the-Art and Future Implications of Simulation-Based Optimization of Logistics Systems with a Special Emphasis on Production Planning and Control Strategies in Manufacturing SMEs

Manuel Woschank (), Michael Kuster, Mario Hoffelner () and Patrick Dallasega ()
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Manuel Woschank: Montanuniversität Leoben, Chair of Industrial Logistics
Michael Kuster: Montanuniversität Leoben, Chair of Industrial Logistics
Mario Hoffelner: Montanuniversität Leoben, Chair of Industrial Logistics
Patrick Dallasega: Free University of Bozen-Bolzano, Faculty of Engineering, Industrial Engineering and Automation (IEA)

Chapter 7 in Industry 5.0 for SMEs, 2026, pp 199-228 from Springer

Abstract: Abstract Using simulation-based optimization offers many opportunities to address key challenges in small and medium-sized enterprises’ production and logistics systems (SMEs). These challenges include improving logistics performance, integrating advanced Industry 4.0/5.0 technologies such as smart systems, and achieving sustainability through decarbonization. Simulation methods, including discrete and continuous approaches, provide tools to model complex systems, evaluate potential improvements, and enhance decision-making. However, barriers such as high costs, required expertise, and concerns about reliability and practical applicability have limited their adoption. This chapter discusses the basics of simulation and optimization tools in logistics systems. Subsequently, the state-of-the-art potential of using simulations is explained based on secondary data and primary data from a case study. Advances in simulation tools, including approaches like KANBAN, CONWIP, and LUMSCOR, are bridging these gaps, enabling more effective production planning and control in dynamic environments. Practical applications demonstrate the transformative potential of these tools to optimize key metrics such as throughput time, delivery reliability, and work-in-progress levels, paving the way for sustainable and human-centered operations in line with Industry 5.0 principles.

Keywords: Simulation; Digital twin; Logistics; Production systems; Logistics 4.0 (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-26279-0_7

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