The effects of pre or post delay variable changes in discrete event simulation and combined DES/system dynamics approaches in modelling supply chain performance

2020 ◽  
pp. 1-19
Author(s):  
Tarek Al-Hawari ◽  
Ahmed Gailan Qasem ◽  
Hazem Smadi ◽  
Haneen Arauydah ◽  
Nader Al Theeb
Keyword(s):  
Supply Chain ◽  
System Dynamics ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Supply Chain Performance ◽  
Event Simulation

Multi-Methodology Approach

2021 ◽  
pp. 98-128
Keyword(s):  
System Dynamics ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Multiple Methods ◽  
Soft Systems ◽  
Agent Based ◽  
Event Simulation ◽  
Pluralistic Approach ◽  
The Difference

The pluralistic approach in today's world needs combining multiple methods, whether hard or soft, into a multi-methodology intervention. The methodologies can be combined, sometimes from several different paradigms, including hard and soft, in the form of a multi-methodology so that the hard paradigms are positivistic and see the organizational environment as objective, while the nature of soft paradigms is interpretive. In this chapter, the combination of methodologies has been examined using soft systems methodologies (SSM) and simulation methodologies including discrete event simulation (DES), system dynamics (SD), and agent-based modeling (ABM). Also, using the ontological, epistemological, and methodological assumptions underlying the respective paradigms, the difference between SD, ABM, SSM; a synthesis of SSM and SD generally known as soft system dynamics methodology (SSDM); and a promising integration of SSM and ABM referred to as soft systems agent-based methodology (SSABM) have been proven.

Network resilience modelling: a New Zealand forestry supply chain case

2020 ◽  
Vol 31 (2) ◽  
pp. 291-311
Author(s):  
Paul Childerhouse ◽  
Mohammed Al Aqqad ◽  
Quan Zhou ◽  
Carel Bezuidenhout
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Supply Chains ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Network Resilience ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Event Simulation ◽  
Export Supply

PurposeThe objective of this research is to model supply chain network resilience for low frequency high impact disruptions. The outputs are aimed at providing policy and practitioner guidance on ways to enhance supply chain resilience.Design/methodology/approachThe research models the resilience of New Zealand's log export logistical network. A two-tier approach is developed; linear programming is used to model the aggregate-level resilience of the nation's ports, then discrete event simulation is used to evaluate operational constraints and validate the capacity of operational flows from forests to ports.FindingsThe synthesis of linear programming and discrete event simulation provide a holistic approach to evaluate supply chain resilience and enhance operational efficiency. Strategically increasing redundancy can be complimented with operational flexibility to enhance network resilience in the long term.Research limitations/implicationsThe two-tier modelling approach has only been applied to New Zealand's log export supply chains, so further applications are needed to insure reliability. The requirement for large quantities of empirical data relating to operational flows limited the simulation component to a single regionPractical implicationsNew Zealand's log export supply chain has low resilience; in most cases the closure of a port significantly constrains export capacity. Strategic selection of location and transportation mode by foresters and log exporters can significantly enhance the resilience of their supply chains.Originality/valueThe use of a two-tiered analytical approach enhances validity as each level's limitations and assumptions are addressed when combined with one another. Prior predominantly theoretical research in the field is validated by the empirical investigation of supply chain resilience.

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