scholarly journals Discrete event simulation of multimodal and unimodal transportation in the wood supply chain: a literature review

Silva Fennica ◽  
2018 ◽  
Vol 52 (4) ◽  
Author(s):  
Christoph Kogler ◽  
Peter Rauch
Keyword(s):  
Supply Chain ◽  
Discrete Event Simulation ◽  
Supply And Demand ◽  
Discrete Event ◽  
Simulation Models ◽  
Forest Products ◽  
Research Area ◽  
Wood Supply ◽  
Event Simulation ◽  
Supply Chain Dynamics

This review systematically analyses and classifies research and review papers focusing on discrete event simulation applied to wood transport, and therefore illustrates the development of the research area from 1997 until 2017. Discrete event simulation allows complex supply chain models to be mapped in a straightforward manner to study supply chain dynamics, test alternative strategies, communicate findings and facilitate understanding of various stakeholders. The presented analyses confirm that discrete event simulation is well-suited for analyzing interconnected wood supply chain transportation issues on an operational and tactical level. Transport is the connective link between interrelated system components of the forest products industry. Therefore, a survey on transport logistics allows to analyze the significance of entire supply chain management considerations to improve the overall performance and not only one part in isolation. Thus far, research focuses mainly on biomass, unimodal truck transport and terminal operations. Common shortcomings identified include rough explanations of simulation models and sparse details provided about the verification and validation processes. Research gaps exist concerning simulations of entire, resilient and multimodal wood supply chains as well as supply and demand risks. Further studies should expand upon the few initial attempts to combine various simulation methods with optimization.

scholarly journals Contingency Plans for the Wood Supply Chain Based on Bottleneck and Queuing Time Analyses of a Discrete Event Simulation

Forests ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 396 ◽  
Author(s):  
Christoph Kogler ◽  
Peter Rauch
Keyword(s):  
Supply Chain ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Management Strategies ◽  
Contingency Planning ◽  
Wood Supply ◽  
Event Simulation ◽  
Contingency Plans ◽  
Value Loss ◽  
Business Cases

Wood supply chain performance suffers from risks intensified by more frequent and extreme natural calamities such as windstorms, bark beetle infestations, and ice-break treetops. In order to limit further damage and wood value loss after natural calamities, high volumes of salvage wood have to be rapidly transported out of the forest. In these cases, robust decision support and coordinated management strategies based on advanced contingency planning are needed. Consequently, this study introduces a contingency planning toolbox consisting of a discrete event simulation model setup for analyses on an operational level, strategies to cope with challenging business cases, as well as transport templates to analyze outcomes of decisions before real, costly, and long-lasting changes are made. The toolbox enables wood supply managers to develop contingency plans to prepare for increasing risk events and more frequent natural disturbances due to climate change. Crucial key performance indicators including truck to wagon ratios, truck and wagon utilization, worktime coordination, truck queuing times, terminal transhipment volume, and required stockyard are presented for varying delivery time, transport tonnage, and train pick-up scenarios. The strategy BEST FIT was proven to provide robust solutions which saves truck and train resources, as well as keeps transhipment volume on a high level and stockyard and queuing time on a low level. Permission granted for increased truck transport tonnages was evaluated as a potential means to reduce truck trips, if working times and train pick-ups are coordinated. Furthermore, the practical applicability for contingency planning is demonstrated by highly relevant business cases such as limited wagon or truck availability, defined delivery quota, terminal selection, queuing time reduction, or scheduled stock accumulation. Further research should focus on the modeling and management of log quality deterioration and the resulting wood value loss caused by challenging transport and storage conditions.

Discrete-event simulation of an information-based raw material allocation process for increasing the efficiency of an energy wood supply chain

2015 ◽  
Vol 149 ◽  
pp. 315-325 ◽  
Author(s):  
Johannes Windisch ◽  
Kari Väätäinen ◽  
Perttu Anttila ◽  
Mikko Nivala ◽  
Juha Laitila ◽  
...  
Keyword(s):  
Supply Chain ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Raw Material ◽  
Wood Supply ◽  
Event Simulation ◽  
Energy Wood ◽  
Allocation Process

scholarly journals Evaluation of a proposed optimization method for discrete-event simulation models

2012 ◽  
Vol 32 (3) ◽  
pp. 543-560 ◽  
Author(s):  
Alexandre Ferreira de Pinho ◽  
José Arnaldo Barra Montevechi ◽  
Fernando Augusto Silva Marins ◽  
Rafael Florêncio da Silva Costa ◽  
Rafael de Carvalho Miranda ◽  
...  
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Simulation Models ◽  
Optimization Method ◽  
Event Simulation

Using Object-Oriented Frame Language for Realizing Discrete Event Simulation

1996 ◽  
Author(s):  
Ming Dong ◽  
Jianzhong Cha ◽  
Mingcheng E
Keyword(s):  
Knowledge Base ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Object Oriented ◽  
Simulation Models ◽  
Activity Cycle ◽  
Event Simulation ◽  
Knowledge Based ◽  
Inference Engines ◽  
Reasoning About Knowledge

Abstract In this paper, we realize knowledge-based discrete event simulation model’s representation, reasoning and implementation by means of object-oriented(OO) frame language. Firstly, a classes library of simulation models is built by using the OO frame language. And then, behaviours of simulation models can be generated by inference engines reasoning about knowledge base. Lastly, activity cycle diagrams can be used to construct simulation network logic models by connecting the components classes of simulation models. This kind of knowledge-based simulation models can effectively solve the modeling problems of complex and ill-structure systems.

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