Holistic, data-driven, service and supply chain optimisation: linked optimisation.

The intensity of competition and technological advancements in the business environment has made companies collaborate and cooperate together as a means of survival. This creates a chain of companies and business components with unified business objectives. However, managing the decision-making process (like scheduling, ordering, delivering and allocating) at the various business components and maintaining a holistic objective is a huge business challenge, as these operations are complex and dynamic. This is because the overall chain of business processes is widely distributed across all the supply chain participants; therefore, no individual collaborator has a complete overview of the processes. Increasingly, such decisions are automated and are strongly supported by optimisation algorithms - manufacturing optimisation, B2B ordering, financial trading, transportation scheduling and allocation. However, most of these algorithms do not incorporate the complexity associated with interacting decision-making systems like supply chains. It is well-known that decisions made at one point in supply chains can have significant consequences that ripple through linked production and transportation systems. Recently, global shocks to supply chains (COVID-19, climate change, blockage of the Suez Canal) have demonstrated the importance of these interdependencies, and the need to create supply chains that are more resilient and have significantly reduced impact on the environment. Such interacting decision-making systems need to be considered through an optimisation process. However, the interactions between such decision-making systems are not modelled. We therefore believe that modelling such interactions is an opportunity to provide computational extensions to current optimisation paradigms. This research study aims to develop a general framework for formulating and solving holistic, data-driven optimisation problems in service and supply chains. This research achieved this aim and contributes to scholarship by firstly considering the complexities of supply chain problems from a linked problem perspective. This leads to developing a formalism for characterising linked optimisation problems as a model for supply chains. Secondly, the research adopts a method for creating a linked optimisation problem benchmark by linking existing classical benchmark sets. This involves using a mix of classical optimisation problems, typically relating to supply chain decision problems, to describe different modes of linkages in linked optimisation problems. Thirdly, several techniques for linking supply chain fragmented data have been proposed in the literature to identify data relationships. Therefore, this thesis explores some of these techniques and combines them in specific ways to improve the data discovery process. Lastly, many state-of-the-art algorithms have been explored in the literature and these algorithms have been used to tackle problems relating to supply chain problems. This research therefore investigates the resilient state-of-the-art optimisation algorithms presented in the literature, and then designs suitable algorithmic approaches inspired by the existing algorithms and the nature of problem linkages to address different problem linkages in supply chains. Considering research findings and future perspectives, the study demonstrates the suitability of algorithms to different linked structures involving two sub-problems, which suggests further investigations on issues like the suitability of algorithms on more complex structures, benchmark methodologies, holistic goals and evaluation, processmining, game theory and dependency analysis

Bio-inspired Computing and Smart Mobility

Por último, se aborda la predicción de plazas libres de aparcamiento utilizando técnicas de aprendizaje automático, tales como series temporales, agrupamiento, etc., incluyendo un prototipo de aplicación web. La tercera parte de esta tesis doctoral se enfoca en el diseño y evaluación de un nuevo algoritmo inspirado en la epigénesis, el Algoritmo Epigenético. Luego de la descripción del modelo en el que se basa y de sus partes, se utiliza este nuevo algoritmo para la resolución del problema de la mochila multidimensional y se comparan sus resultados con los de otros algoritmos del estado de arte. Por último se emplea también el Algoritmo Epigenético para la optimización de la arquitectura Yellow Swarm, un problema de movilidad inteligente resuelto por un nuevo algoritmo bioinspirado. A lo largo de esta tesis doctoral se han descrito los problemas de movilidad inteligente y propuesto nuevas herramientas para su optimización. A partir de los experimentos realizados se concluye que estas herramientas, basadas en algoritmos bioinspirados, son eficientes para abordar estos problemas, obteniendo resultados competitivos comparados con los del estado del arte, los cuales han sido validados estadísticamente. Esto representa un aporte científico pero también una serie de mejoras para la sociedad toda, tanto en su salud como en el aprovechamiento de su tiempo libre. Fecha de lectura de Tesis: 01 octubre 2018.Esta tesis doctoral propone soluciones a problemas de movilidad inteligente, concretamente la reducción de los tiempos de viajes en las vías urbanas, las emisiones de gases de efecto invernadero y el consumo de combustible, mediante el diseño y uso de nuevos algoritmos bioinspirados. Estos algoritmos se utilizan para la optimización de escenarios realistas, cuyo trazado urbano se obtiene desde OpenStreetMap, y que son luego evaluados en el microsimulador SUMO. Primero se describen las bases científicas y tecnológicas, incluyendo la definición y estado del arte de los problemas a abordar, las metaheurísticas que se utilizarán durante el desarrollo de los experimentos, así como las correspondientes validaciones estadísticas. A continuación se describen los simuladores de movilidad como principal herramienta para construir y evaluar los escenarios urbanos. Por último se presenta una propuesta para generar tráfico vehicular realista a partir de datos de sensores que cuentan el número de vehículos en la ciudad, utilizando herramientas incluidas en SUMO combinadas con algoritmos evolutivos. En la segunda parte se modelan y resuelven problemas de movilidad inteligente utilizando las nuevas arquitecturas Red Swarm y Green Swarm para sugerir nuevas rutas a los vehículos utilizando nodos con conectividad Wi-Fi. Red Swarm se centra en la reducción de tiempos de viajes evitando la congestión de las calles, mientras que Green Swarm está enfocado en la reducción de emisiones y consumo de combustible. Luego se propone la arquitectura Yellow Swarm que utiliza una serie de paneles LED para indicar desvíos que los vehículos pueden seguir en lugar de nodos Wi-Fi haciendo esta propuesta más accesible. Además se propone un método para genera rutas alternativas para los navegadores GPS de modo que se aprovechen mejor las calles secundarias de las ciudades, reduciendo los atascos

The application of information technologies to public transportation

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1994.Includes bibliographical references (leaves 2218-222).by Chi Fun Jimmy Lam.M.S

Digital Literacy in der beruflichen Lehrer:innenbildung

Kompetenzanforderungen in kaufmännischen Ausbildungen verändern sich durch die Digitalisierung von Wirtschaftsprozessen und Geschäftsmodellen. Für die erfolgreiche Vermittlung dieser digitalen Kompetenzen muss die Lehrkräftebildung für berufsbildende Schulen angepasst werden. Dazu diskutieren die Beiträge des Sammelbandes die digitale Literalität der Lehrkräfte aus theoretisch-empirischer und erfahrungspraktischer Perspektive. Themen sind der Aufbau von digitaler Kompetenz sowie Orientierungswissen über digital strukturierte Wertschöpfungsprozesse bei Berufsschulehrkräften. Die Beiträge zur Digital Literacy sind unter vier Aspekten zusammengefasst: domänenspezifische Konzepte, didaktische Innovationen, empirische Ergebnisse über Studierende und Lehrkräfte sowie digitale Literalität in Bildungsentwicklungsprozessen. Das Thema digitale Literalität hat disziplinübergreifend eine hohe Relevanz für alle, die sich wissenschaftlich und praktisch mit der Lehrkräftebildung beschäftigen

Airlines, with Conforming Changes as of March 1, 2013; Audit and accounting Guide

https://egrove.olemiss.edu/aicpa_indev/2254/thumbnail.jp

Digital Literacy in der beruflichen Lehrer:innenbildung

Kompetenzanforderungen in kaufmännischen Ausbildungen verändern sich durch die Digitalisierung von Wirtschaftsprozessen und Geschäftsmodellen. Für die erfolgreiche Vermittlung dieser digitalen Kompetenzen muss die Lehrkräftebildung für berufsbildende Schulen angepasst werden. Dazu diskutieren die Beiträge des Sammelbandes die digitale Literalität der Lehrkräfte aus theoretisch-empirischer und erfahrungspraktischer Perspektive. Themen sind der Aufbau von digitaler Kompetenz sowie Orientierungswissen über digital strukturierte Wertschöpfungsprozesse bei Berufsschulehrkräften. Die Beiträge zur Digital Literacy sind unter vier Aspekten zusammengefasst: domänenspezifische Konzepte, didaktische Innovationen, empirische Ergebnisse über Studierende und Lehrkräfte sowie digitale Literalität in Bildungsentwicklungsprozessen. Das Thema digitale Literalität hat disziplinübergreifend eine hohe Relevanz für alle, die sich wissenschaftlich und praktisch mit der Lehrkräftebildung beschäftigen

Proceedings of the Eleventh Annual Precise Time and Time Interval (PTTI) Application and Planning Meeting

Thirty eight papers are presented addressing various aspects of precise time and time interval applications. Areas discussed include: past accomplishments; state of the art systems; new and useful applications, procedures, and techniques; and fruitful directions for research efforts

Electricity transmission line planning: Success factors for transmission system operators to reduce public opposition

Europe requires significant transmission grid expansions to foster the integration of electricity markets, enhance security of supply and integrate renewable energies. However, next to lengthy authorization processes, transmission system operators (TSOs) in Europe are currently facing extreme public opposition in their transmission line projects leading to significant project delays. These delays imply significant additional costs for TSOs as well as society as a whole and put the transformation of the European energy system at risk. Existing scientific literature currently lacks comprehensive studies that have tried to identify generalizable success factors to overcome public opposition in transmission line projects. The goal of work at hand was to close this research gap. Potential success factors were collected through extensive literature review and interviews throughout Europe with respective stakeholders such as citizen action groups, NGOs or energy experts. Experiences from analogue large infrastructure projects like wind parks, carbon capture and storage facilities, hydro dams, nuclear waste repositories, etc. were also used to form hypotheses. The findings were transformed into a structural equation model and tested through a questionnaire answered by almost all European TSOs. Results revealed that people’s trust in the TSO is of utmost importance for less public opposition. It can be regarded as the critical success factor per se. TSOs can create trust through stakeholder participation, sufficient communication, proper organizational readiness and liaison with stakeholders. Furthermore, appropriate technical planning can help to reduce public opposition in transmission line projects. In total 18 concrete and actionable success factors were identified for TSO management to facilitate the establishment of these aforementioned aspects. They will help European TSOs to reduce public opposition and thus accelerate the implementation of new transmission lines. Interestingly, economic benefits for people did not turn out to be a Significant success factor in reducing their opposition against new transmission lines.:Contents I List of tables VIII List of figures IX List of abbreviations XI List of symbols XV List of country codes XVI 1 Introduction 1 1.1 Problem statement 1 1.2 Thematic classification and research gap 2 1.3 Objective, research questions and scop e of work 3 1.4 Methodology and structure of work 5 2 Fundamentals of electricity transmission line planning 7 2.1 History of the European electricity transmission network 7 2.2 Transmission technologies 9 2.2.1 High-voltage alternating current (HVAC) 9 2.2.1.1 High - voltage alternating current overhead lines (HVAC OHL) 9 2.2.1.2 High - voltage alternating underground cables (HVAC UGC) 10 2.2.2 High - voltage direct current (HVDC) 12 2.2.2.1 High - voltage direct current overhead lines (HVDC OHL) 12 2.2.2.2 High - voltage direct current underground cables (HVDC UGC) 13 2.2.3 Gas - insulated lines (GIL) 14 2.3 Major players 15 2.3.1 European Transmission System Operators (TSOs) and related associations 15 2.3.1.1 National Transmission System Operators (TSOs) 15 2.3.1.2 ENTSO - E 16 2.3.2 Energy regulators and related associations 18 2.3.2.1 National regulatory authorities (NRA) 18 2.3.2.2 European associations of energy regulators 19 2.4 Development of new transmission lines 20 2.4.1 Planning objectives 20 2.4.2 Planning process 21 2.4.2.1 Identification of needs 22 2.4.2.2 Feasibility study 23 2.4.2.3 Spatial planning 24 2.4.2.4 Strategic Environmental Assessment (SEA) 25 2.4.2.5 Environmental Impact Assessment (EIA) 26 2.4.2.6 Permitting procedure 28 2.4.2.7 Securing land rights and way - leaves 28 2.4.2.8 Construction, commissioning and operation 29 2.5 Project delays and obstacles 31 2.5.1 Project delays 31 2.5.2 Rationales for delay 33 2.5.2.1 Minor obstacles 34 2.5.2.2 Public opposition 35 2.5.2.3 Insufficient authorization procedures 36 2.5.3 Excursus: Recent governmental measures to overcome delays 38 2.5.3.1 Austria 38 2.5.3.2 Denmark 38 2.5.3.3 Germany 39 2.5.3.4 Great Britain 41 2.5.3.5 Netherlands 42 2.5.3.6 European Union 43 2.5.3.7 Further recommendations 48 2.6 Interim conclusion on the fundamentals of transmission line planning 49 3 Fundamentals of social acceptance 51 3.1 Definition and classification 51 3.2 Contextual factors that influence stakeholders’ attitudes 54 3.2.1 Proximity of stakeholders to a facility 54 3.2.2 Risk perception of individuals 55 3.2.3 Individual knowledge base 56 3.2.4 Existing and marginal exposure 56 3.2.5 Land valuation and heritage 57 3.2.6 Trust in project developer 58 3.2.7 Energy system development level 59 3.3 The history of social movement against infrastructure facilities 60 3.4 Forms of public opposition 61 3.5 Interim conclusion on the fundamentals of social acceptance 63 4 Fundamentals and methodology of success factor research 64 4.1 The goal of success factor research 64 4.2 Defining success factor terminology 64 4.2.1 Success 64 4.2.2 Success factors 65 4.3 Success factor research history and current state 67 4.4 Classification of success factor studies 67 4.4.1 Specificity 68 4.4.2 Causality 69 4.5 Success factor identification approaches 70 4.5.1 Systematization of success factor identification approaches 70 4.5.2 Approach assessment 72 4.6 Criti cism to success factor research 73 4.7 Interim conclusion on the fundamentals of success factor research 75 5 Success factor res earch on social acceptance in transmission line planning – a combination of research streams 77 5.1 State of research 77 5.1.1 Social acceptance in electricity transmission line planning (A) 77 5.1.2 Success factor research on social acceptance (B) 83 5.1.3 Success factor research in transmission line planning (C) 89 5.2 Value add and classification of this work 89 5.3 Research design 90 5.3.1 Identification of potential success factors through a direct, qualitative - explorative approach 92 5.3.1.1 Overview of methodologies 92 5.3.1.2 Survey 93 5.3.2 Quantitative - confirmatory approach to validate potential success factors 95 5.3.2.1 Overview of statistical methodologies 95 5.3.2.2 Structural equation modeling (SEM) 96 5.3.2.2.1 Path analysis 97 5.3.2.2.2 Structure of SEM 99 5.3.2.2.3 Methods for SEM estimation 102 5.3.2.2.4 PLS algorithm 106 6 Identification of reasons for public opposition and derivation of potential success factors 112 6.1 Conducted interviews 112 6.1.1 Selection of interviewees 112 6.1.2 Preparation, conduction and documentation of interviews 115 6.2 Reasons for public opposition 117 6.2.1 Health and safety issues 118 6.2.1.1 Electric and magnetic fields (EMF) 118 6.2.1.2 Falling ice 124 6.2.1.3 Toppled pylons and ruptured conductors 125 6.2.1.4 Flashover 125 6.2.2 Reduced quality of living 126 6.2.2.1 Visual impact 126 6.2.2.2 Noise 128 6.2.3 Economic unfairness 130 6.2.3.1 Devaluation of property and insufficient compensation 130 6.2.3.2 Expropriation 131 6.2.3.3 Negative impact on tourism 132 6.2.3.4 Lack of direct benefits and distributional unfairness 132 6.2.3.5 Agricultural disadvantages 133 6.2.4 Lack of transparency and communication 135 6.2.4.1 Insufficient justification of line need 135 6.2.4.2 Insufficient, inaccurate and late information 137 6.2.4.3 Intransparent decision making 138 6.2.4.4 Inappropriate appearance 138 6.2.4.5 Expert dilemma 139 6.2.5 Lack of public participation 140 6.2.5.1 Lack of involvement 140 6.2.5.2 One - way communication 141 6.2.5.3 Lack of bindingness 141 6.2.5.4 Inflexibility 142 6.2.6 Environmental impact 142 6.2.6.1 Flora 143 6.2.6.2 Fauna 145 6.2.7 Distrust 146 6.3 Potential success factors to reduce public opposition 147 6.3.1 Communication 149 6.3.1.1 Communication strategy 149 6.3.1.2 Early communication 150 6.3.1.3 Line justification 150 6.3.1.4 Direct personal conversation 151 6.3.1.5 Appropriate communication mix 153 6.3.1.6 Comprehensibility 156 6.3.1.7 Sufficient and honest information 157 6.3.1.8 Stakeholder education 158 6.3.1.9 Post - communication 159 6.3.2 Participation 160 6.3.2.1 Pre - polls 160 6.3.2.2 Participation possibilities 161 6.3.2.3 Participation information 164 6.3.2.4 Macro - planning involvement 165 6.3.2.5 Pre - application involvement 166 6.3.2.6 Neutral moderation/mediation 166 6.3.2.7 Joint fact finding 169 6.3.2.8 Flexibility, openness and respect 170 6.3.2.9 Commitment and bindingness 171 6.3.2.10 Transparent decision making 172 6.3.3 Economic benefits 173 6.3.3.1 Local benefits 173 6.3.3.2 Individual compensations 174 6.3.3.3 Muni cipality compensations 176 6.3.3.4 Socio - economic benefits 177 6.3.3.5 Excursus: Social cost - benefit analysis of a new HVDC line between France and Spain 177 6.3.4 Organizational readiness 182 6.3.4.1 Stakeholder analysis and management 182 6.3.4.2 Qualification and development 184 6.3.4.3 Sufficient resources 186 6.3.4.4 Internal coordination 187 6.3.4.5 Cultural change 187 6.3.4.6 Top - management support 188 6.3.4.7 Best practice exchange 188 6.3.5 Stakeholder liaison 189 6.3.5.1 Stakeholder cooperation 189 6.3.5.2 Supporters / Multiplicators 190 6.3.5.3 Local empowerment 191 6.3.6 Technical planning 191 6.3.6.1 Line avoidance options 191 6.3.6.2 Route alternatives 194 6.3.6.3 Transmission technology options 194 6.3.6.4 Piloting of innovations 198 6.3.6.5 Excursus: Exemplary transmission line innovations 198 6.3.6.6 Avoidance of sensitive areas 206 6.3.6.7 Bundling of infrastructure 206 6.3.6.8 Line deconstruction 207 6.3.6.9 Regulatory overachievement 208 7. Development of research model 209 7.1 Procedure 209 7.2 Development of hypotheses on causal relationships 209 7.2.1 Stakeholder liaison 209 7.2.2 Participation 210 7.2.3 Communication 210 7.2.4 Organizational readiness 211 7.2.5 Economic benefits 212 7.2.6 Technical planning 212 7.2.7 Trust 213 7.2.8 Summary of hypotheses 213 7.3 Development of path diagram and model specification 214 7.3.1 Structural model 214 7.3.2 Measurement model 215 7.3.2.1 Formative measurements 215 7.3.2.2 Reflective measurements 2 7.4 Identifiability of model structure 217 8 Empirical validation of potential success factors 219 8.1 Data acqu isition 219 8.1.1 Concept of using questionnaires for data acquisition 219 8.1.2 Target group and sample size 220 8.1.3 Questionnaire design 222 8.1.3.1 Form and structure 222 8.1.3.2 Operatio nalization 224 8.1.3.2.1 Operationalization of potential success factors 224 8.1.3.2.2 Operationalization of construct TRUST 225 8.1.3.2.3 Operationalization of construct REDUCED PUBLIC OPPOSITION 226 8.1.3.2.4 Operationalization of control variables 226 8.1.3.3 Bias 227 8.1.3.3.1 Common method bias 227 8.1.3.3.2 Key i nformation bias 229 8.1.3.3.3 Hypothetical bias 229 8.1.4 Pretest 230 8.1.5 Questionnaire return and data preparation 231 8.2 Model estimation 236 8.2.1 Software selection for modeling 236 8.2.2 Estimation results 237 8.3 Model evaluation 239 8.3.1 Evaluat ion of reflective measurement models 240 8.3.1.1 Content validity 240 8.3.1.2 Indicator reliability 243 8.3.1.3 Construct validity 245 8.3.1.3.1 Convergent validity 245 8.3.1.3.1.1 Average var iance extracted (AVE) 245 8.3.1.3.1.2 Construct reliability 245 8.3.1.3.2 Discriminant validity 247 8.3.1.3.2.1 Fornell/Larcker criterion 247 8.3.1.3.2.2 Cross loadings 248 8.3.2 Evaluation of formative measurement models 250 8.3.2.1 Content validity 250 8.3.2.2 Indicator reliability / relevance 250 8.3.2.2.1 Indicator weights and significance 250 8.3.2.2.2 Multicollinearity 254 8.3.2.3 Construct validity 256 8.3.3 Evaluation of structural model 256 8.3.3.1 Multicollinearity 256 8.3.3.2 Explanatory power 257 8.3.3.3 Predictive relevance 259 8.3.4 Evaluation of total model 260 8.4 Verification of hypotheses and discussion of results 260 8.5 Success factors for reducing public opposition in transmission line planning: Recommendations for TSO management 264 8.5.1 Measures to create stakeholder trust 266 8.5.1.1 Sufficient stakeholder participation 266 8.5.1.2 Proper stakeholder communication 267 8.5.1.3 TSO’s organizational readiness for stakeholder management 267 8.5.1.4 Creating liaison with stakeholders 268 8.5.2 Important aspects in technical planning 268 8.5.3 Consolidated overview 269 9 Concluding remarks 270 9.1 Summary of results 270 9.2 Contribution, limitations, and directions for further research 272 10 Appendix 27