Title: A resource allocation model to choose the best portfolio of economic resilience plans: a possibilistic stochastic programming model

Authors: Shima Pashapour; Ali Azadeh; Ali Bozorgi-Amiri; Abbas Keramati; Seyed Farid Ghaderi

Addresses: School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran ' Deceased; formerly of: School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran ' School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran ' School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran; Ted Rogers School of Information Technology Management, Ryerson University, Toronto, ON, Canada ' School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Abstract: Economic resilience is defined as a tool capable of reducing the losses caused by disasters. It can be defined in two major concepts. Static economic resilience is the effective allocation of available resources and dynamic economic resilience refers to accelerating the recovery process through the repair and rebuilding of the capital stock. In this research, the performance of a petrochemical plant in the face of crisis is investigated. For this, a bi-objective mathematical model that considers cost and resilience capability as objective functions is developed to choose the best portfolio of static and dynamic plans. To solve the mathematical model, a weighted augmented ε-constraint method and a multi-stage possibilistic stochastic programming (MSPSP) approach are employed. The numerical results showed that the proposed approach is effective in optimising the performance of a petrochemical plant in facing crisis situations and in choosing the best portfolio of economic resilience plans. [Received: 11 January 2019; Revised: 9 July 2019; Revised: 13 August 2019; Accepted: 13 August 2019]

Keywords: economic resilience; resilience capability; multi-stage possibilistic stochastic programming; MSPSP; petrochemical plant; resource allocation.

DOI: 10.1504/EJIE.2020.107669

European Journal of Industrial Engineering, 2020 Vol.14 No.3, pp.301 - 334

Published online: 08 Jun 2020 *

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