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Abstract: The functionality of infrastructures, particularly in densely populated areas, is greatly impacted by natural disasters, resulting in uncertain networks. Thus, it is important for crisis management professionals and computer-based systems for transportation networks (such as expert systems) to utilize trustworthy data and robust computational methodologies when addressing convoluted decision-making predicaments concerning the design of transportation networks and optimal routes. This study aims to evaluate the vulnerability of paths in post-disaster transportation networks, with the aim of facilitating rescue operations and ensuring the safe delivery of supplies to affected regions. To investigate the problem of links' tolerances in uncertain networks and the resiliency and reliability of paths, an uncertainty theory-based model that employs minmax optimization with a bottleneck objective function is used. The model addresses the uncertain maximum reliable paths problem, which takes into account uncertain risk variables associated with links. Rather than using conventional methods for calculating the deterministic tolerances of a single element in combinatorial optimization, this study introduces a generalization of stability analysis based on tolerances while the perturbations in a group of links are involved. The analysis defines set tolerances that specify the minimum and maximum values that a designated group of links could simultaneously fluctuate while maintaining the optimality of the max-type reliable paths. The study shows that set tolerances can be considered as well-defined and proposes computational methods to calculate or bound such quantities - which were previously unresearched and difficult to measure. The model and methods are demonstrated to be both theoretically and numerically efficient by applying them to four subnetworks from our case study. In conclusion, this study provides a comprehensive approach to addressing uncertainty in reliability problems in networks, with potential applications in various fields.
Keywords: Disaster Management, Network Reliability, Stability Analysis, Transportation, Uncertainty
Published in RUNG: 24.11.2023; Views: 139; Downloads: 0
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Keywords: strateško načrtovanje, izobraževalni programi, izobraževalna tehnologija, digitalna tehnologija, management, e-learning planning, e-learning programmes, digital society, educational technology
Published in RUNG: 03.03.2023; Views: 687; Downloads: 15
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Keywords: Disaster Management, Transportation, Optimization, Uncertainty, Reliability, Stability Analysis
Published in RUNG: 14.02.2023; Views: 532; Downloads: 0
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Abstract: The need for a Circular Economy became more than obvious, and in line with that, technologies for utilization of renewables and waste-to-energy transformation have become of utmost importance in climate change mitigation. This master thesis deals with treating the waste after olive oil extraction and using anaerobic digestion to turn the waste into a biogas that later can be used for electricity and heat production. Since there are two options for location, it was necessary to use decision support models to remove subjectivity and bias from the decision-making process. After the decision was made, there was an economic analysis of a biogas plant project that later can be used for establishing a new company in Italy. According to the economic indicators, with a profit of 5.243.000 EUR after ten years and an investment return of less than five years, a biogas plant in Italy is a profitable investment. From the aspect of Circular Economy, the biogas plant successfully fits the concept. It has added value to the local community by turning one process by-product into primary material for another process, creating jobs and generating revenue for the municipal budget while preserving natural resources.
Keywords: circular economy, decision support models, biogas, strategic management
Published in RUNG: 11.07.2022; Views: 1379; Downloads: 58
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Abstract: Namen magistrske naloge je bila analiza kapitalske strukture v slovenskih podjetjih za posamezno dejavnost in njene povezanosti z ekonomsko uspešnostjo. V raziskavi smo obravnavali približno 1 % vseh slovenskih podjetij v obdobju med letoma 2015 in 2019 ter iskali povezanost med kazalniki uspešnosti, kot so kazalnik donosnosti lastniškega kapitala, kazalnik donosnosti sredstev ter kazalniki zadolženosti. Poleg tega smo z analizo varianc primerjali zadolženost podjetij med letoma in zadolženost podjetij med Standardnimi klasifikacijami dejavnosti 2008. Ugotovili smo, da ni statistično značilne povezanosti med kazalniki uspešnosti in kazalniki zadolženosti sredstev. Pri zadolženosti podjetij smo ugotovili, da se med letoma statistično značilno razlikujejo vsi obravnavani kazalniki zadolženosti sredstev. Ugotovili smo tudi, da se zadolženost podjetij med dejavnostmi statistično značilno razlikuje. S širšo analizo stopnje zadolževanja ter njenega vpliva na kazalnike uspešnosti po dejavnostih se odpirajo številne možnosti za nadaljnje raziskave in potencialno okvirna določitev pričakovane ravni zadolževanja po panogah, kar predstavlja koristen pripomoček za kreditodajalce in kreditojemalce.
Keywords: ekonomija, donosnost, finance, kapitalska struktura, management, podjetje, zadolženost
Published in RUNG: 03.05.2021; Views: 1914; Downloads: 115
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