The Supply Security Problem and its Solution

Main Article Content

Rolan J. Malvar, Alsafat M. Abdul, Paul Ryan A. Longhas

Abstract

This study introduces a mathematical model to address the supply security problem, a critical issue in today’s global landscape. Furthermore, we present a method for efficiently identifying optimal solutions to security assignment problems, which holds significant implications for various sectors, including business and policy-making, particularly in the context of food security and supply security. Leveraging fundamental principles of convex optimization, such as proximity operators and projection onto convex sets, this study not only identifies instances where optimal solutions to security problems exist but also provides an explicit formula for the solution when it exists. Additionally, we establish the existence of pseudo-solutions in security assignment problems and demonstrate that they coincide with actual solutions when present. A key highlight of this paper is its pioneering application of convex optimization techniques to address security challenges.

Article Details

References

  1. World Bank, Food Security Update | World Bank Solutions to Food Insecurity, https://www.worldbank.org/en/topic/agriculture/brief/food-security-update.
  2. M.E. Biresselioglu, T. Yelkenci, I.O. Oz, Investigating the Natural Gas Supply Security: A New Perspective, Energy 80 (2015), 168-176. https://doi.org/10.1016/j.energy.2014.11.060.
  3. M. Mohsin, P. Zhou, N. Iqbal, S.A.A. Shah, Assessing Oil Supply Security of South Asia, Energy 155 (2018), 438-447. https://doi.org/10.1016/j.energy.2018.04.116.
  4. A. Correljé, C. van der Linde, Energy Supply Security and Geopolitics: A European Perspective, Energy Policy 34 (2006), 532-543. https://doi.org/10.1016/j.enpol.2005.11.008.
  5. S. Gyamfi, M. Modjinou, S. Djordjevic, Improving Electricity Supply Security in Ghana—The Potential of Renewable Energy, Renew. Sustain. Energy Rev. 43 (2015), 1035-1045. https://doi.org/10.1016/j.rser.2014.11.102.
  6. L. Martisauskas, J. Augutis, Mathematical Modelling of Security of Energy Supply Disturbance Scenarios, in: 6th Annual Conference of Young Scientists on Energy Issues, Kaunas, Lithuania, 2009. https://hdl.handle.net/20.500.12259/57217.
  7. A. Rogachev, E. Antamoshkina, Mathematical Modeling of the Food-Security Level Using a Fuzzy Cognitive Approach, IOP Conf. Ser. Earth Environ. Sci. 403 (2019), 012181. https://doi.org/10.1088/1755-1315/403/1/012181.
  8. R. Babazadeh, J. Razmi, M. Rabbani, M.S. Pishvaee, An Integrated Data Envelopment Analysis–Mathematical Programming Approach to Strategic Biodiesel Supply Chain Network Design Problem, J. Clean. Prod. 147 (2017), 694-707. https://doi.org/10.1016/j.jclepro.2015.09.038.
  9. H.H. Bauschke, P.L. Combettes, Convex Analysis and Monotone Operator Theory in Hilbert Spaces, Springer, 2017. https://doi.org/10.1007/978-3-319-48311-5.
  10. Y. Yu, The proximity operator. Carnegie Mellon University, https://www.cs.cmu.edu/~suvrit/teach/yaoliang_proximity.pdf.
  11. J. Dattorro, Convex Optimization & Euclidean Distance Geometry, Meboo Publishing USA, 2005.