Reducing the Bullwhip effect in a supply chain network by application of optimal control theory

Abstract

Controlling the bullwhip effect and reducing the propagated inventory levels throughout the supply chain layers has an important role in reducing the total inventory costs of a supply chain. In this study, an optimal controller that considers demand as control variable is designed to dampen propagated inventory fluctuations for each node throughout the supply chain network. The model proves to be very useful in revealing the dynamic characteristics of the chain and provides a proper interface to study decisions taken into account at each node of the supply chain in different periods by decision makers (DMs). In the proposed approach, two feedback loops and online updated values of net stock quantities are used for calculation of the orders. To investigate the efficiency of the proposed approach, a real case of bicycle industry is conducted. The acquired results justify the efficiency of the proposed approach in controlling and dampening the bullwhip effect and reducing inventory levels, net stock quantities and inventory attributed costs throughout the supply chain network layers.

The bullwhip effect: causes, intensity, and mitigation

“…To accomplish these outcomes this article briefly summarized here some historical premises & definitions for the concept of BWE and showed the significance of BWE in supply chain followed by critical appraisal of various methods. Sabbaghnia et al (2018) developed an optimal controller by the application of optimal control theory considering demand as a control variable to dampen inventory propagation throughout the SC networks that reveals its dynamic characteristics and provides the perfect interface for the decision-makers (DMs). The impact of BWE & inventory propagation was explored by Hussain and Saber (2012) considering batching & information sharing with multi-echelon SC using simulation and Taguchi experimental design and found non-monotonic relation between batch size & demand amplification.…”

“…The impact of BWE & inventory propagation was explored by Hussain and Saber (2012) considering batching & information sharing with multi-echelon SC using simulation and Taguchi experimental design and found non-monotonic relation between batch size & demand amplification. Sabbaghnia et al (2018), Saber (2012) &Drake (2011) contributed to control BWE providing practical ways/approaches to the SC operations managers to understand its impact on SC excellence. The subjectivity of DMs was assessed by fuzzy logic and a supplier selection problem was solved by the development of a new ranking method on the basis of a fuzzy inference system (FIS) (Amindoust et al, 2012).…”

Deploying Big Data Enablers to Strengthen Supply Chain Agility to Mitigate Bullwhip Effect: An Empirical Study of China’s Electronic Manufacturers

“…Dai et al, 2017 used case analysis to show that inventory strategy in supplier management is an effective way to reduce the bullwhip effect [59]. Sabbaghnia et al, 2018 treated order demand as the best controller to suppress inventory fluctuations at each node in the entire supply chain network, thereby controlling the bullwhip effect [118]. Ojha et al, 2019 used a simulation study to verify that using information sharing to coordinate orders in a supply chain can reduce the negative effects of the bullwhip effect [119].…”

Local Blood Supply Chain Optimization: A Case Study

“…rijqijt ≤ r0; ∀i, j, t (9) r1 ik q1 ikt ≤ r10; ∀i, k, t (10) Ujwt ≤ M.qijt; ∀i, j, w, t (11) Y kwt ≤ M.q1 ikt ; ∀i, k, w, t (12) qijt ≤ x1jt; ∀i, j, t…”

“…The network design problem of the blood supply chain is different from other business-oriented problems because of the deteriorative nature of blood. For more details on the design challenges of business-oriented supply chain networks, interested readers can refer to the literature (8)(9)(10). In this regard, Pereira (11) used a data envelopment analysis (DEA) model to compare technical efficiency rather than economic efficiency for the establishment of a regional blood center in the United States.…”