Interpreting supply chain dynamics: A quasi-chaos perspective

Hwarng, H. Brian; Yuan, Xuchuan

doi:10.1016/j.ejor.2013.09.025

Cited by 36 publications

(34 citation statements)

References 29 publications

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“…By inserting CLIP functions ( to avoid order rates reaching negative values (also referred to as forbidden return constraint) and shipments being made without any on-hand inventory, the model in Figure 1 has been used to replicate the Beer Game (Spiegler and Naim, 2014). Other OUT systems that consider some of these nonlinearities include Laugesen and Mosekilde (2006); Mosekilde and Laugesen (2007); Wang and Disney (2012); Hwarng and Yuan (2014); Wang et al (2015b) More recently, a similar model has been identified in the replenishment system of a grocery retailer (Spiegler et al, 2016b), but, in addition to the non-negativity constraint, orders were also batched based on the buying quantities and truckload limits.…”

Section: Model Formulation: Nonlinear Production and Inventory Contromentioning

confidence: 99%

Investigating sustained oscillations in nonlinear production and inventory control models

Spiegler

Naim

2017

European Journal of Operational Research

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Even in a deterministic setting, nonlinearities can yield unexpected dynamic behaviours in a production and inventory control system, such as sustained oscillations or limit cycles. Describing function in combination with simulation is used to analyse the e↵ect of discontinuous nonlinearities on the system responses. Utilising a nonlinear production and inventory control model, we investigate the occurrence of limit cycles and propose a technique to predict their amplitude, frequency and stability and to control such oscillations. Findings suggest that, even for an autonomous production and inventory control system, limit cycles do occur and this periodic behaviour occurs due to non-negativity constraint in the ordering rule. Moreover, we demonstrate the potential of the describing function method to provide insight into the impact of system constraints and therefore facilitate a more e↵ective system design. This paper fills a gap in the literature on nonlinear supply chain dynamics by expanding and complementing the sparse recent research in this area. Most previous studies have either focused on linear mathematical models or relied on simulation, which greatly limit the relevancy and/or rigour of the published results.

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Section: Model Formulation: Nonlinear Production and Inventory Contromentioning

confidence: 99%

Investigating sustained oscillations in nonlinear production and inventory control models

Spiegler

Naim

2017

European Journal of Operational Research

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“…H. Hwarng and X. Yuan (2014) found the chaotic phenomena, chaos amplification and other nonlinear behaviors in supply chain systems. They derived that the effective inventory at different supply chain levels demonstrated various chaotic dynamics that depended on specific deterministic demand settings [1]. Scientists showed different asymmetric and nonlinear properties in behavior main macroeconomic indicators that evaluated economic development and stability in Ukraine as well as in European countries [2; 3].…”

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confidence: 99%

System Dynamic Nonlinear Modeling of Price Stability

Kozytskyi

Beregova

Pabyrivska

2020

PSAE

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Козицький В.А. кандидат фізико-математичних наук, доцент, доцент кафедри математичної економіки та економетрії Львівського національного університету імені Івана Франка Берегова Г.І. кандидат фізико-математичних наук, доцент, доцент кафедри обчислювальної математики та програмування Національного університету «Львівська політехніка» Пабирівська Н.В. кандидат фізико-математичних наук, доцент, доцент кафедри вищої математики Національного університету «Львівська політехніка» SYSTEM DYNAMIC NONLINEAR MODELING OF PRICE STABILITY СИСТЕМНЕ ДИНАМІЧНЕ НЕЛІНІЧНЕ МОДЕЛЮВАННЯ ЦІНИ СТАБІЛЬНОСТІThe article investigates the dynamic properties of price indexes based on the system dynamics approach that is a simulation modeling approach to monetary policy analysis and design. It applies to dynamic problems that describe complex economic and social systems including information and material delays as well as feedback and circular causality. The simulation nonlinear model takes into account the nonlinear process of price adjustment. The simulation results showed that the behavior of price indexes could change dramatically that was driving by small change in initial conditions and parameters of system. It has been obtained that the inflation process looked often as unpredictable and chaotic system although it had underlying sources and its driving forces did not demonstrate pure randomness. The price dynamics should be considered in a system and dynamic view and it is important to estimate the direction and magnitudes of unemployment and inflation responses on positive and negative economic shocks.

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“…The Beer Game is also used as an experimental platform in many studies to investigate the behavior of supply chains under many different settings. One of the main reasons of the wide use of The Beer Game is that it is capable of producing complex dynamics as demonstrated by many studies (Hwarng & Xie, 2008;Hwarng & Yuan, 2014;Mosekilde & Laugesen, 2007;Thomsen, Mosekilde, & Sterman, 1991).…”

Section: Introductionmentioning

confidence: 99%