A new dynamic optimisation model for operational supply chain recovery

Abstract

This paper focuses on the problem of dynamic supply chain (SC) recovery. We consider effectiveness and efficiency of various reactive measures to recover the SC with the minimum cost at the operational level. For this purpose, a new general model based on bounded optimal control theory is developed to determine the type, the extent, and the timing of reactive measures. We demonstrate its application using an example of a two-echelon poultry SC. The intention of the proposed model is to optimise both the recovery and its costs simultaneously. The developed model is solved exactly using the Pontryagin’s maximum principle. We performed a set of sensitivity analyses to illustrate the model's behaviour. The results obtained from applying the dynamic recovery model in the case study show that the proposed model can help SC managers to deal with disruptions by comparing alternative recovery options, based on two important criteria of the time and cost of SC's recovery. The findings of this research advocate the consideration of dynamic SC characteristics and the need for simultaneous attention to the effectiveness and efficiency of reactive measures in recovery planning.

KEYWORDS:

• Disruption
• supply chain resilience
• bounded optimal control
• dynamic supply chain recovery
• reactive measures

Disclosure statement

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

Additional information

Notes on contributors

Alireza Khamseh

Alireza Khamseh is a doctoral student in Industrial Engineering at Iran University of Science and Technology (IUST), Tehran, Iran. He holds a Bachelor degree in industrial engineering (2005), and obtained his master degree in industrial engineering in 2007. He served as an industrial engineer and production planner (2008–2016) in different industries. His current research interests lie in the areas of operations and supply chain management, production planning and scheduling, and dynamic systems.

Ebrahim Teimoury

Ebrahim Teimoury is an Associate Professor in the Department of Industrial Engineering, Iran University of Science and Technology (IUST), Tehran, Iran. He received his PhD from IUST in 2000. He has worked with many businesses and public sectors. His main scientific interests are directed to supply chain management, socio-economic systems modelling, performance measurement system, and queuing theory. He is author (or co-author) of more than 100 scientific papers, referee for more than 5 international scientific journals.

Kamran Shahanaghi

Kamran Shahanaghi is an Associate Professor in the Department of Industrial Engineering, Iran University of Science and Technology (IUST), Tehran, Iran. He received his PhD from IUST in 2000. He teaches simulation, uncertain programming, Multi-criteria decision making (MCDM), and system dynamics courses and his current research interests are: reverse logistics, crisis management, reliability, and maintenance. He has published more than 40 international research papers.