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Tadeusz Sawik
Professor of Industrial and Systems Engineering
AGH University of Science and Technology
http://home.agh.edu.pl/~tsawik
SUPPLY CHAIN DISRUPTION MANAGEMENT USING A MULTI-PORTFOLIO APPROACH
A new portfolio approach is presented to support decision-making in the presence of supply chain disruption risks. Unlike most of reported research on supply chain disruption management a disruptive event is assumed to impact both a primary supplier of parts and the buyer's firm primary assembly plant. Then the firm may choose alternate (recovery) suppliers and move production to alternate (recovery) plants along with transshipment of parts from the impacted primary plant to the recovery plants. For the impacted suppliers and assembly plants, both time and cost of recovery from disruption is considered. The resulting allocation of unfulfilled demand for parts among recovery suppliers and unfulfilled demand for products among recovery assembly plants determines recovery supply and demand portfolio, respectively. Scenario-based stochastic mixed integer programming formulations with an embedded network flow problem are developed for selection of primary suppliers, the decision to be implemented before a disruption and for selection of recovery suppliers and recovery assembly plants, the decision to be implemented during and after the disruption. Local and regional, two- and multi-level disruptions of suppliers and assembly plants are considered. The selection of supply, transshipment and demand portfolios is determined simultaneously with production scheduling in assembly plants. The two decision-making approaches will be considered: an integrated approach with the perfect information about the future disruption scenarios, and a hierarchical approach with no such information available ahead of time. In the integrated approach a two-stage stochastic model is applied, in which the first stage decision considers disruption scenarios to happen in the second stage so that the impact of disruption risks is mitigated. The second stage decision optimizes the supply chain recovery process. The integrated approach accounts for all potential disruption scenarios. The primary supply portfolio that will hedge against all scenarios is determined along with the recovery supply and demand portfolios and production schedule of finished products for each scenario. In the hierarchical approach first the primary supply portfolio is selected to optimize supplies and production in deterministic conditions (without a disruption) and then, when a primary supplier or primary assembly plant is hit by a disruption, the recovery supply and demand portfolios are determined along with transshipment of parts and production schedule at recovery plants to optimize the process of recovery from the disruption, given the unfulfilled demand for products and the inventory of parts at the primary assembly plant. The integrated decision-making selects a more diversified primary supply portfolio to hedge against all potential disruption scenarios. When all primary suppliers are completely shutdown, a single sourcing recovery supply portfolio is usually selected. If all assembly plants are shutdown, the integrated approach may select the primary plant as a single recovery plant, whereas the hierarchical approach may choose multiple recovery plants. The scenario analysis indicates that for the hierarchical approach the best-case and worst-case disruption scenarios are, respectively subsets and supersets of the corresponding scenarios for the integrated approach. In addition to risk-neutral decision-making based on expected cost or expected service level optimization, an integrated risk-averse approach is developed using Conditional Value-at- Risk as a risk measure. Several modifications of the proposed portfolio approach will be discussed, including selection of a resilient supply portfolio with fortified suppliers and prepositioning of emergency inventory of parts and selection of a dynamic supply portfolio under delay and disruption risks. A multi-period stochastic formulation will be compared with a simplified two-period model, where the multi-period production decisions are replaced by a simplified two-period decision: production before and production after a disruptive event. Computational results will be presented and discussed. The findings indicate that the developed multi-portfolio approach leads to computationally efficient mixed integer programming models with a very strong LP relaxation.
Keywords: supply chain risk management, disruption mitigation and recovery, primary portfolio, recovery portfolio, stochastic mixed integer programming
References
1. Sawik, T.: Selection of supply portfolio under disruption risks. Omega, 39(2011), 194-208.
2. Sawik, T.: Selection of resilient supply portfolio under disruption risks. Omega, 41(2013), 259 –
269.
3. Sawik, T.: Selection of optimal countermeasure portfolio in IT security planning. Decision Support
Systems, 55(2013), 156-164.
4. Sawik, T.: A portfolio approach to supply chain disruption management. International Journal of
Production Research, 55(2017), 1970 - 1991.
5. Sawik, T.: Selection of a dynamic supply portfolio under delay and disruptions risks.. International
Journal of Production Research, 56(2018), 758 - 780.
6. Sawik, T.: Supply Chain Disruption Management Using Stochastic Mixed Integer Programming.
Springer International Series in Operations Research and Management Science, vol.256, New York,
2018.
About the speaker
Professor Tadeusz Sawik
Tadeusz Sawik is a Professor of Industrial Engineering and Operations Research at AGH University of Science and Technology in Kraków, Poland. He received the MS degree in mechanical engineering, the PhD degree in automation engineering and the ScD (habilitation) degree in operations research, all from AGH University. He has been a visiting professor in Germany, Japan, Sweden and Switzerland and he has served as a research advisor of Motorola for several years. He is also a five-time recipient of the Scientific Excellence Individual Award from the Minister of Science and Higher Education, one of the most prestigious award in Poland, and over 25-time from the Rector of AGH. Professor Sawik works in the area of logistics and supply chain management, with a particular recent focus on supply chain risk management. He is the first researcher to apply the financial engineering percentile risk measures, Value-at-Risk and Conditional Value-at-Risk in the context of supply disruptions and one of the first researchers who investigated multi-level (partial) disruption risks. His current research interests also include cybersecurity and homeland security. He has published numerous books (including 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, 2018), and more than 150 individual articles in refereed journals, including Highly Cited papers in Economics & Business of the Thomson Reuters Essential Science Indicators database. In the 50th and 55th volume anniversary issue of International Journal of Production Research, he has been recognized as one of the leading scholars in Production Research. He is the founding Editor-in-Chief of Decision Making in Manufacturing and Services (AGH University Press).