Publication:
Optimising the preparedness capacity of enterprise resilience using mathematical programming

Loading...
Thumbnail Image
Identifiers
Publication date
2020-09
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Impact
Google Scholar
Export
Research Projects
Organizational Units
Journal Issue
Abstract
In today's volatile business arena, companies need to be resilient to deal with the unexpected. One of the main pillars of enterprise resilience is the capacity to anticipate, prevent and prepare in advance for disruptions. From this perspective, the paper proposes a mixed-integer linear programming (MILP) model for optimising preparedness capacity. Based on the proposed reference framework for enterprise resilience enhancement, the MILP optimises the activation of preventive actions to reduce proneness to disruption. To do so, the objective function minimizes the sum of the annual expected cost of disruptive events after implementing preventive actions and the annual cost of such actions. Moreover, the algorithm includes a constraint capping the investment in preventive actions and an attenuation formula to deal with the joint savings produced by the activation of two or more preventive actions on the same disruptive event. The management and business rationale for proposing the MILP approach is to keep it as simple and comprehensible as possible so that it does not require highly mathematically skilled personnel, thus allowing top managers at enterprises of any size to apply it effortlessly. Finally, a real pilot case study was performed to validate the mathematical formulation.
Description
This article belongs to the Special Issue Mathematical Methods and Analysis for the Industrial Management and Business.
Keywords
Enterprise resilience, Mathematical programming, MILP, Optimisation, Preparedness
Bibliographic citation
Sanchis, R., Duran-Heras, A., & Poler, R. (2020). Optimising the preparedness capacity of enterprise resilience using mathematical programming. Mathematics, 8(9), 1596.