Integrated approaches for logistics network planning: a systematic literature review

Abstract

Researchers and practitioners often separate logistics network planning into strategic, tactical, and operational decisions. Due to the interdependence among these levels of decisions, their integration can bring important cost reductions and better network responsiveness in scenarios where there is business change. However, integrated problems entail challenges, such as decision timing, and they are more difficult to model and solve. This article presents a literature review of integrated problems in logistics network planning. The objective is to identify the main integrated decisions, their scopes, integration approaches, and the solution methods used. Although this review addresses research with decisions at different hierarchical planning levels, we observed that integration of strategic and tactical decisions is more common and some of the integration approaches are single-level mono-period models, single-level multi-period models, multi-time scale models, and multi-level models. There is a predominance of aggregated data in these studies. Regarding the solution methods, there is a predominance of heuristic approaches over exact ones, including methods based on decomposition or sequential procedures. Based on the findings of this systematic review, we draw a conceptual framework presenting the main modelling assumptions, integration strategies, and solution methods to the integrated problems, and we also discuss some promising research opportunities.

Keywords:

• Logistics network
• integrated planning
• supply chain management
• optimisation
• systematic literature review

Acknowledgments

The authors would like to thank the anonymous reviewers for their useful comments and suggestions or revision.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was partially financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001; São Paulo Research Foundation (FAPESP) [grant number 2016/01860-1], [grant number 2017/07236-0], [grant number 2018/09563-1].

Notes on contributors

Aura Maria Jalal

Aura Jalal, MSc, is a doctoral student at Department of Production Engineering, Federal University of São Carlos, in Brazil. Her research interests are focused on location and distribution problems, inventory management, robust optimisation, stochastic programming, reverse logistics, and exact and heuristic solution methods such as Bender's decomposition, matheuristic, and hybrid methods.

Eli Angela Vitor Toso

Eli Angela Vitor Toso is an associated professor at the Production Engineering Department of the Federal University of São Carlos – campus Sorocaba, in Brazil. She received her BSc's degree, master's degree, and doctorate, all in production engineering from the Federal University of São Carlos. Also, she attended a split PHD program at University of the West of England, in Bristol, UK. Eli Toso has developed projects with companies and public institutions focusing on applied operations research. Her research interests comprise logistics network design and production planning problems, mainly to understand how to address these problems in practical contexts. Her other scientific interests rely on optimisation models and solution methods applied to the integration of strategic, tactical, and operational decisions.

Reinaldo Morabito

Reinaldo Morabito is a professor at the Production Engineering Department of the Federal University of São Carlos, in Brazil. He earned a B.S. in Civil Engineering from the State University of Campinas, an M.Sc. in Computer Science and Computational Mathematics and a Ph.D. in Transportation Engineering, both from the University of Sao Paulo, Brazil. He was a visiting scholar at the Sloan School of Management, M.I.T., Cambridge, MA. Prof. Morabito has coordinated many grants from funding agencies and has developed applied projects with several companies in Brazil, with a focus on Operations Research, Service and Operations Management, Production and Logistics Planning and Control. His research interests include logistics and transportation planning including vehicle routing problems, probabilistic location problems, cutting and packing problems, lot sizing, and scheduling problems, and queueing networks applied to manufacturing systems. Additionally, he has worked on combinatorial optimisation, stochastic programming, and robust optimisation.