Risk-averse decision-making to maintain supply chain viability under propagated disruptions

Abstract

In this paper, stochastic optimisation of CVaR is applied to maintain risk-averse viability and improve resilience of a supply chain under propagated disruptions. In order to establish the risk-averse boundaries on supply chain viability space, two stochastic optimisation models are developed with the two conflicting objectives: minimisation of Conditional Cost-at-Risk and maximisation of Conditional Service-at-Risk. Then, the risk-averse viable production trajectory between the two boundaries is selected using a stochastic mixed integer quadratic programming model. The proposed approach is applied to maintain the supply chain viability in the smartphone manufacturing and the results of computational experiments are provided. The findings indicate that when the decision-making is more risk-aversive, the size of the viability space between the two boundaries is greater. As a result, more room is available for selecting viable production trajectories under severe disruptions. Moreover, the larger is viability space, the higher is both worst-case and average resilience of the supply chain. Risk-neutral, single-objective decision-making may reduce the supply chain viability. A single-objective supply chain optimisation which moves production to the corresponding boundary of the viability space, should not be applied under severe disruption risks to avoid greater losses.

Keywords:

• Supply chain disruption management
• supply chain viability
• supply chain resilience
• stochastic mixed integer linear programming
• stochastic mixed integer quadratic programming

Acknowledgments

The authors acknowledge the helpful comments and clarification requests by the Associate Editor and two anonymous reviewers.

Disclosure statement

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

Data availability statement

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Additional information

Notes on contributors

Tadeusz Sawik

Tadeusz Sawik is a Professor of Industrial Engineering and Operations Research in the Department of Engineering, Reykjavik University in Reykjavik, Iceland, and at AGH University of Science and Technology in Kraków, Poland. He received the MS degree in Automation Engineering, the PhD degree in Operations Engineering and the Habilitation degree in Operations Research, all from AGH University. He has been a visiting professor in France, Germany, Greece, Japan, Portugal, Spain, Sweden and Switzerland and has served as a research advisor of Motorola for several years. He is the sole author of numerous books, including Analysis and Synthesis of Multivariable Control Systems, AGH University Press 1984, Discrete Optimization in Flexible Manufacturing Systems, WNT Publishers 1992, Operations Research for Industrial Engineers, AGH University Press 1998, Production Planning and Scheduling in Flexible Assembly Systems, Springer 1998, Scheduling in Supply Chains Using Mixed Integer Programming, Wiley 2011 and Supply Chain Disruption Management Using Stochastic Mixed Integer Programming, Springer 1st edition 2018, 2nd edition 2020, and more than 150 individual articles in many prestigious journals. He has been a recipient of various individual awards for research achievements, including five times of Scientific Excellence Award from the Minister of Science and Higher Education and over 25 times of Scientific Award from the Rector of AGH. In the World's Top 2% Scientists list recently released by Stanford University and published in PloS Biology, ranked #144 in Operations Research until the end of 2021, and #71 during the single calendar year 2021. His current research interests include logistics and supply chain management, supply chain risk management, cyber and homeland security, planning and scheduling, mixed integer programming, stochastic and combinatorial optimisation.

Bartosz Sawik

Dr Bartosz Sawik is a Professor at the Department of Business Informatics and Engineering Management, AGH University of Science and Technology, Krakow, Poland and at the Institute of Smart Cities, GILT-OR Group, Department of Statistics, Computer Science and Mathematics, Public University of Navarre, Pamplona, Spain. He is a Visiting Researcher at the University of California, Berkeley, USA. He has a Ph.D. and a M.Sc. and Eng. in Operations Engineering, all with honors at the Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, AGH University. He has also finished Executive Course on Strategic Leadership in University Management at the University of Helsinki, Finland, Executive Course on Master of Didactics in Excellent Teaching at Aarhus University, Denmark and Executive Course on Innovation and New Technology in Science at HAAS School of Business, University of California at Berkeley, USA. He has been an Invited Researcher at the University of California, Berkeley, USA, Universidad Publica de Navarra, Pamplona, Spain, Universitat Politecnica de Valencia, Alcoi, Spain and Internet Interdisciplinary Institute (IN3) - Open University of Catalonia (UOC), Castelldefels, Barcelona, Spain. He is a member of HAROSA research group (UOC Barcelona, Spain) and CYTED-HAROSA research group (UPNA Pamplona, Spain). He has published several individual articles in refereed journals and individual refereed chapters in books indexed in JCR and Scopus. He has been a Principal Investigator in one research grant in Poland and and Investigator in additional six research projects (two in Poland and four in Spain). He has been PhD Thesis Co-Advisor (Finished): 2 (Poland) and PhD Thesis External Reviewer (Finished): 3 (Spain). He is an Expert in The National Centre for Research and Development (NCBiR) in Poland and in The Polish Agency for Enterprise Development (PARP). He also is a Representative of the National Center for Research and Development (NCBiR) on the supervisory board of the Bridge-Alpha investment funds. He has been a recipient of various individual awards including Polish Ministry of Science & Higher Education (MNISW) ‘Top 500 Innovators’. His current research interests include multi-criteria optimisation, mixed integer programming, stochastic and combinatorial optimisation, portfolio and risk optimisation, green vehicle routing problems, cyber security optimisation, automated parcel lockers optimal allocation in urban areas, and decision support systems for finance, logistics, healthcare, and supply chain.