An enhanced robustness approach for managing supply and demand uncertainties

Abstract

Managing supply and demand uncertainties is a topic that receives increasing management attention due to (1) more price-based competitions forcing firms purchase from cheaper but less-reliable or unproven suppliers, and (2) undesirable consequences of unaddressed demand fluctuations such as reduced service level, financial loss, reputational damage, and loss of market share. This paper presents a realistic production–distribution planning model that is robust to common supply interruptions and demand variations. A robustness approach, named “Elastic p-Robustness”, is introduced that obviates the need to estimate probability distribution of random parameters when managing operational uncertainties of the supply chain. The application of the proposed approach is investigated in an actual organization from discrete, durable parts manufacturing sector. Our analyses of numerical results focus on (1) exploring different tactics for managing supply and demand variations, (2) examining the benefits of concurrent consideration of supply and demand uncertainties, (3) benchmarking the performance of the proposed approach against the popular robustness algorithms, and (4) investigating the price of robustness under various supply and demand scenarios.