Simulation optimization in inventory replenishment: a classification

Abstract

Simulation optimization is increasingly popular for solving complicated and mathematically intractable business problems. Focusing on academic articles published between 1998 and 2013, the present survey aims to unveil the extent to which simulation optimization has been used to solve practical inventory problems (as opposed to small, theoretical “toy problem”), and to detect any trends that might have arisen (e.g., popular topics, effective simulation optimization methods, frequently studied inventory system structures). We find that metaheuristics (especially genetic algorithms) and methods that combine several simulation optimization techniques are the most popular. The resulting categorizations provide a useful overview for researchers studying complex inventory management problems, by providing detailed information on the inventory system characteristics and the employed simulation optimization techniques, highlighting articles that involve stochastic constraints (e.g., expected fill rate constraints) or that employ a robust simulation optimization approach. Finally, in highlighting both trends and gaps in the research field, this review suggests avenues for further research.

Keywords:

• Inventory management
• simulation optimization
• robust simulation optimization

Additional information

Notes on contributors

Hamed Jalali

Hamed Jalali received his M.S. degree in Statistics (Cum laude) from KU Leuven in 2013 and is currently a Ph.D. student at the Research Centre for Operations Management, Faculty of Economics and Business, KU Leuven. His general research interests include simulation optimization (especially using metamodel-based techniques) and inventory management in the presence of manufacturer and consumer-driven substitution.

Inneke Van Nieuwenhuyse

Inneke Van Nieuwenhuyse is Associate Professor of Operations Management at the Research Centre for Operations Management, KU Leuven, Belgium. She received her Ph.D. from the University of Antwerp (Belgium) in 2004. Her research interests focus on the design and analysis of stochastic manufacturing and supply chain systems and on simulation optimization.