A Fuzzy Logic Approach to Prove Bullwhip Effect in Supply Chains

The bullwhip effect in nowadays Supply Chains has become a major source of problems and has attracted supply chain scientists attentions. This paper explores the concept of bullwhip effect in supply chains throughout a completely new approach. Assuming all demands are fuzzy in supply chain, fuzzy If-Then rules are used to show the bullwhip effect. Application of fuzzy logic is due to the fuzzy nature of supply chain problems. The new approach can be the source of inspiration for new solutions to the bullwhip effect in supply chains base on fuzzy logic and fuzzy If-Then rules. Fuzzy time series are widely used in this paper. First for data generation, we apply a modified version of Hwang fuzzy time series with a neural network for defuzzification and finally to show the bullwhip effect, we use Lee fuzzy time series which is based on Fuzzy If-Then rules, Genetic Algorithm and Simulated Annealing

A Fuzzy Logic Approach to Prove Bullwhip Effect in Supply Chains

The bullwhip effect in nowadays Supply Chains has become a major source of problems and has attracted supply chain scientists attentions. This paper explores the concept of bullwhip effect in supply chains throughout a completely new approach. Assuming all demands are fuzzy in supply chain, fuzzy If-Then rules are used to show the bullwhip effect. Application of fuzzy logic is due to the fuzzy nature of supply chain problems. The new approach can be the source of inspiration for new solutions to the bullwhip effect in supply chains base on fuzzy logic and fuzzy If-Then rules. Fuzzy time series are widely used in this paper. First for data generation, we apply a modified version of Hwang fuzzy time series with a neural network for defuzzification and finally to show the bullwhip effect, we use Lee fuzzy time series which is based on Fuzzy If-Then rules, Genetic Algorithm and Simulated Annealing

A Study of the Impact of Information Blackouts on the Bullwhip Effect of a Supply Chain Using Discrete-Event Simulations

This study adds to the supply chain management literature by introducing and investigating information blackouts, sudden and short-duration failure of the information flow. This study aims to contribute to the literature in following ways: first, to define information blackouts in a supply chain. Second, to investigate the response of supply chains to information blackouts using discrete-event simulation. Prior research has focused more on analyzing systemic disruptions to supply chains from well-known sources. We expect the results of this study to be useful to supply chain managers in disaster prone areas

Closed-loop supply chains: What reverse logistics factors influence performance?

This paper analyses the inventory and order flow dynamics in closed-loop supply chains (CLSCs). In this kind of supply chains the reverse flow of materials entering the system for recycling purposes complicates the way in which inventories should be managed and replenishment policies should be designed. Specifically, we analyse the relationships between some reverse logistics' factors (remanufacturing lead-time, return rate of recycled products, reverse order policy, and number of supply chain tiers) on the order and inventory variance amplification. We firstly perform a systematic literature review of the related studies. Secondly, by adopting a difference equation math approach and design of experiment we perform a robust what-if analysis of a CLSC under a variety of operational and market conditions. Results show that, ceteris paribus, CLSC outperforms a forward supply chain, both in mono-echelon and multi-echelon structures and under both stationary and turbulent market demands. Furthermore, reducing remanufacturing lead-time and promoting information transparency may be crucial to improve CLSC dynamics. Finally, we use the research findings to provide interesting managerial consideration about how to reduce unnecessary operational members' costs

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems