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1.
A system dynamics approach to decision-making tools in farm tourism development
Maja Borlinič Gačnik, Črtomir Rozman, Andrej Škraba, Boris Prevolšek, 2020, original scientific article

Abstract: Background: Besides visiting the main tourist attractions in Slovenia, many tourists want to spend their free time in the countryside as well, but the number of farming establishments in Slovenia diminished distinctly in the last years. Objectives: This paper aims to develop a system dynamics model, with the goal to analyse dynamics of the diversification of agricultural holdings into farm tourism activities in Slovenia. Methods/Approach: A system dynamics methodology was chosen to model the diversification in farm tourism. First, we present a basic concept of a system dynamics model with a causal loop diagram. Further, a system dynamics model with different scenarios is presented. Results: The main feedback loops were identified, and the simulation model was used to analyse different simulation scenarios of the transition of farming establishments into farm tourism facilities. Conclusions: The model provides the answers to the strategic questions about the dynamics of transfer into tourist farms, using several simulation scenarios. The transition mainly relies on subsidies, promotion of diversification and the growth of rural tourism, which provides a relevant direction for the development of future incentives.
Keywords: farm tourism, rural tourism, modelling, system dynamics, causal loop diagram, simulation
Published in DKUM: 13.01.2025; Views: 0; Downloads: 2
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2.
Developing a diversification strategy of non-agricultural activities on farms using system dynamics modelling : a case study of Slovenia
Maja Borlinič Gačnik, Boris Prevolšek, Karmen Pažek, Črtomir Rozman, Andrej Škraba, 2022, original scientific article

Abstract: Purpose: This paper aims to analyse the main variables and causal relationships in the system structure of the diversification of non-agricultural activities on agricultural holdings using system dynamics (SD) modelling. The SD model aims to simulate depictions of the behaviour of the real system while testing the effects of alternative decisions over time. Design/methodology/approach: An SD methodology was chosen to model diversification in farm tourism. Findings: A system approach increases the authors’ understanding of the transition of agricultural holdings to farm tourism. The results indicate that the transition to farm tourism depends on the level of tourism development in a certain area. The system is influenced by subsidies allocated by authorities to expand primary agricultural activities. The model describes a situation in which the tourism and agricultural industries have been affected by the COVID-19 pandemic. Research limitations/implications: The research is limited by the small set of available data due to the limited number of farms in Slovenia. One major problem is the difference in statistical data on the same activity collected from different institutions in Slovenia. Practical implications: The paper includes implications for understanding the transition process to farm tourism, allowing policymakers to experiment with subsidies and promotion to explore the efficacy and efficiency of proposed policies. Originality/value: This study provides a structured, systemic view of the diversification of non-agricultural activities on agricultural holdings, where the simulation results are a reliable reflection of the behaviour of the actual system being modelled.
Keywords: system dynamics, modelling, simulation, diversification, farm tourism, farm policy, Slovenia, simulation scenarious
Published in DKUM: 11.12.2024; Views: 0; Downloads: 2
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3.
Optimizing smart manufacturing systems using digital twin
Robert Ojsteršek, Aljaž Javernik, Borut Buchmeister, 2023, original scientific article

Abstract: Presented paper investigates the application of digital twins for the optimisation of intelligent manufacturing systems and focuses on the comparison between simulation modelling results and real-world production conditions. A digital twin was created in the Simio software environment using a data-driven simulation model derived from a real-world production system. Running the digital twin in real time, which was displayed graphically, facilitated the analysis of key parameters, including the number of finished products, average flow time, workstation utilization and product quality. The discrepancies were attributed to the use of random distributions of input data in the dynamic digital twin, as opposed to the long-term measurements and averages in the real-world system. Despite the limitations in the case study, the results underline the financial justification and predictive capabilities of digital twins for optimising production systems. Real-time operation enables continuous evaluation and tracking of parameters and offers high benefits for intelligent production systems. The study emphasises the importance of accurate selection of input data and warns that even small deviations can lead to inaccurate results. Finally, the paper high-lights the role of digital twins in optimising production systems and argues for careful consideration of input data. It highlights the importance of analysing real-world production systems and creating efficient simulation models as a basis for digital twin solutions. The results encourage extending the research to different types of production, from job shop to mass production, in order to obtain a comprehensive optimisation perspective.
Keywords: smart manufacturing, digital twin, optimisation, simulation modelling, Simio, case study
Published in DKUM: 25.03.2024; Views: 277; Downloads: 17
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4.
Managing the complexity of empty container movements through repositioning strategies and routing practices under certain demand and supply : doctoral dissertation
Alaa Abdelshafie, 2023, doctoral dissertation

Abstract: Over the past decades, container transportation management has become an important part of the global maritime industry. Due to an ever-increasing movement of containers across the globe in line with the economic boom, the trade imbalance and issues related to empty containers have become inevitable. The accumulation of empty containers in specific ports not only causes a waste of money but also increases the environmental footprint. Accordingly, the urgent need for empty container management has been gaining more attention than ever before, as the shipping companies recognized that more revenues are always derived from a good repositioning strategy. In this respect, this thesis described state-of-the-art of empty container management, focusing on the practices concerning the movement of empty containers that are varied between organizational policies, technical solutions, and optimization applications. With the development of computer-aided systems, the combination of optimization and simulation models has been proposed to tackle the maritime empty container problem. The thesis shows how the strengths of optimization-based simulation can be integrated to provide high-quality solutions with low computational costs. Agent-based modelling was developed to model the global movements of empty containers, providing realistic details of interactions among entities and characteristics of components within the system. The model was applied between ports in the Middle East and Asia for one of the biggest shipping lines worldwide. By using simulated annealing (SA), the best sequence for moving containers can be determined. The results comparison demonstrate that the proposed optimised repositioning strategy can significantly reduce the shipping line’s costs and make full use of empty containers in the planning horizon.
Keywords: shipping industry, container transportation management, empty container repositioning, simulation, optimization, agent-based modelling
Published in DKUM: 08.12.2023; Views: 579; Downloads: 24
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5.
Simulated global empty containers repositioning using agent-based modelling
Alaa Abdelshafie, Bojan Rupnik, Tomaž Kramberger, 2023, original scientific article

Abstract: Due to an ever-increasing movement of containers across the globe in line with the economic boom, the trade imbalance and issues related to empty containers have become inevitable. Empty containers accumulated at specific ports cannot only generate profit but also increase the environmental footprint. This research proposes a Maritime Empty Container Reposition Modelling Framework by integrating the agent-based modelling (ABM) paradigm to model the global movements of empty containers. An agent-based maritime logistic empty container redistribution model was developed to help minimize the total relevant costs for empty container movement in the planning horizon. In the system, ports, shipping companies, customers, and empty containers were identified as critical agents. Using simulated annealing (SA), shipping line agents were able to optimise empty container repositioning to determine the best sequence for moving containers. The model was applied to the Asia–Middle East region to simulate global empty containers repositioning in the region. The results comparison shows that the proposed optimised empty container repositioning framework can significantly reduce the shipping line’s costs and make full use of empty containers
Keywords: maritime industry, empty containers, repositioning, agent-based modelling, simulation, optimisation
Published in DKUM: 02.08.2023; Views: 396; Downloads: 43
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Industry 4.0 and the new simulation modelling paradigm
Blaž Rodič, 2017, original scientific article

Abstract: Background and Purpose: The aim of this paper is to present the influence of Industry 4.0 on the development of the new simulation modelling paradigm, embodied by the Digital Twin concept, and examine the adoption of the new paradigm via a multiple case study involving real-life R&D cases involving academia and industry. Design: We introduce the Industry 4.0 paradigm, presents its background, current state of development and its influence on the development of the simulation modelling paradigm. Further, we present the multiple case study methodology and examine several research and development projects involving automated industrial process modelling, presented in recent scientific publications and conclude with lessons learned. Results: We present the research problems and main results from five individual cases of adoption of the new simulation modelling paradigm. Main lesson learned is that while the new simulation modelling paradigm is being adopted by big companies and SMEs, there are significant differences depending on company size in problems that they face, and the methodologies and technologies they use to overcome the issues. Conclusion: While the examined cases indicate the acceptance of the new simulation modelling paradigm in the industrial and scientific communities, its adoption in academic environment requires close cooperation with industry partners and diversification of knowledge of researchers in order to build integrated, multi-level models of cyber-physical systems. As shown by the presented cases, lack of tools is not a problem, as the current generation of general purpose simulation modelling tools offers adequate integration options.
Keywords: simulation, modelling, automated modelling, Industry 4.0, Digital Twin, SME, multiple-case study
Published in DKUM: 30.11.2017; Views: 1571; Downloads: 526
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9.
A statistical model for shutdowns due to air quality control for a copper production decision support system
Khalid Aboura, 2015, original scientific article

Abstract: Background: In the mid-1990s, a decision support system for copper production was developed for one of the largest mining companies in Australia. The research was conducted by scientists from the largest Australian research center and involved the use of simulation to analyze options to increase production of a copper production facility. Objectives: We describe a statistical model for shutdowns due to air quality control and some of the data analysis conducted during the simulation project. We point to the fact that the simulation was a sophisticated exercise that consisted of many modules and the statistical model for shutdowns was essential for valid simulation runs. Method: The statistical model made use of a full year of data on daily downtimes and used a combination of techniques to generate replications of the data. Results: The study was conducted with a high level of cooperation between the scientists and the mining company. This contributed to the development of accurate estimates for input into a support system with an EXCEL based interface. Conclusion: The environmental conditions affected greatly the operations of the production facility. A good statistical model was essential for the successful simulation and the high budget expansion decision that ensued.
Keywords: decision support system, simulation, statistical modelling
Published in DKUM: 28.11.2017; Views: 1317; Downloads: 340
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10.
Roundabout arm capacity determined by microsimulation and discrete functions technique
Tomaž Tollazzi, Matjaž Šraml, Tone Lerher, 2008, original scientific article

Abstract: The paper demonstrates the influence of the multi-channel pedestrian flow on the actual capacity of a one-lane roundabout, using micro-simulation and discrete functions. The proposed model is based on the theory of the expected time gap between the units of pedestrian traffic flow, which have the priority when crossing the arm of the roundabout. The proposed model represents an upgrade of the previous research in the field of modelling traffic flows in the one-lane roundabout.Apart from the multi-channel pedestrian flow the disturbances caused by the circular traffic flow of motorised vehicles at the roundabout are also considered. In this way the model can better illustrate the real conditions in traffic. A simulation analysis has been performed on the roundabout arm at Koroška Street in Maribor. The results of the analysis have indicated a relatively high reserve of the actual throughput capacity for the main motorized traffic flow in the analysed roundabout arm. The presented model represents a practicable and adaptable tool for planning the roundabout capacity in practice and for the sensitivity analysis of individual variables on the throughput capacity of the roundabout.
Keywords: roundabouts, traffic flow analysis, micro-simulation modelling, capacity analysis
Published in DKUM: 05.06.2017; Views: 1583; Downloads: 174
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