Angel A. Juan – författare

In real-life scenarios, service management involves complex decision-making processes usually affected by random or stochastic variables. Under such uncertain conditions, the development and use of robust and flexible strategies, algorithms, and methods can provide the quantitative information necessary to make better business decisions. Decision Making in Service Industries: A Practical Approach explores the challenges that must be faced to provide intelligent strategies for efficient management and decision making that will increase your organization’s competitiveness and profitability.The book provides insight and understanding into practical and methodological issues related to decision-making processes under uncertainty in service industries. It examines current and future trends regarding how these decision-making processes can be efficiently performed for better design of service systems by using probabilistic algorithms as well as hybrid and simulation-based approaches.Traditionally, many quantitative tools have been developed to make decisions in production companies. This book explores how to use these tools for making decisions inside service industries. Thus, the authors tackle strategic, tactical, and operational problems in service companies with the help of suitable quantitative models such as heuristic and metaheuristic algorithms, simulation, or queuing theory. Generally speaking, decision making is a hard task in business fields. Making the issue more complex, most service companies’ problems are related to the uncertainty of the service demand. This book sheds light on these types of decision problems. It provides studies that demonstrate the suitability of quantitative methods to make the right decisions. Consequently, this book presents the business analytics needed to make strategic decisions in service industries.

In real-life scenarios, service management involves complex decision-making processes usually affected by random or stochastic variables. Under such uncertain conditions, the development and use of robust and flexible strategies, algorithms, and methods can provide the quantitative information necessary to make better business decisions. Decision Making in Service Industries: A Practical Approach explores the challenges that must be faced to provide intelligent strategies for efficient management and decision making that will increase your organization’s competitiveness and profitability.The book provides insight and understanding into practical and methodological issues related to decision-making processes under uncertainty in service industries. It examines current and future trends regarding how these decision-making processes can be efficiently performed for better design of service systems by using probabilistic algorithms as well as hybrid and simulation-based approaches.Traditionally, many quantitative tools have been developed to make decisions in production companies. This book explores how to use these tools for making decisions inside service industries. Thus, the authors tackle strategic, tactical, and operational problems in service companies with the help of suitable quantitative models such as heuristic and metaheuristic algorithms, simulation, or queuing theory. Generally speaking, decision making is a hard task in business fields. Making the issue more complex, most service companies’ problems are related to the uncertainty of the service demand. This book sheds light on these types of decision problems. It provides studies that demonstrate the suitability of quantitative methods to make the right decisions. Consequently, this book presents the business analytics needed to make strategic decisions in service industries.

Simulation Methods for Reliability and Availability of Complex Systems discusses the use of computer simulation-based techniques and algorithms to determine reliability and availability (R and A) levels in complex systems. The book: shares theoretical or applied models and decision support systems that make use of simulation to estimate and to improve system R and A levels, forecasts emerging technologies and trends in the use of computer simulation for R and A and proposes hybrid approaches to the development of efficient methodologies designed to solve R and A-related problems in real-life systems.Dealing with practical issues, Simulation Methods for Reliability and Availability of Complex Systems is designed to support managers and system engineers in the improvement of R and A, as well as providing a thorough exploration of the techniques and algorithms available for researchers, and for advanced undergraduate and postgraduate students.

Hybrid Algorithms for Service, Computing and Manufacturing Systems: Routing and Scheduling Solutions explores research developments and applications from an interdisciplinary perspective that combines approaches from operations research, computer science, artificial intelligence, and applied computational mathematics. Contributions cover a range of hybrid algorithm theory and practice as it relates to routing, scheduling, and real-life applications.

Simulation Methods for Reliability and Availability of Complex Systems discusses the use of computer simulation-based techniques and algorithms to determine reliability and availability (R and A) levels in complex systems. The book: shares theoretical or applied models and decision support systems that make use of simulation to estimate and to improve system R and A levels, forecasts emerging technologies and trends in the use of computer simulation for R and A and proposes hybrid approaches to the development of efficient methodologies designed to solve R and A-related problems in real-life systems.Dealing with practical issues, Simulation Methods for Reliability and Availability of Complex Systems is designed to support managers and system engineers in the improvement of R and A, as well as providing a thorough exploration of the techniques and algorithms available for researchers, and for advanced undergraduate and postgraduate students.

This book constitutes the proceedings of the Second Decision Science Alliance International Summer Conference, DSA ISC 2024, held in Valencia, Spain, in June 2024.The 33 full papers and 38 short papers included in this book were carefully reviewed and selected from 101 submissions.At the core of DSA ISC’24 are in-depth discussions and analyses across a spectrum of technological domains. Notably, experts shared their knowledge on areas such as Artificial Intelligence & Machine Learning, Mathematical Optimization, Operational Research & Management Science, Statistics, Simulation, and Decision Processes Analysis. Each of these areas represents a key aspect of decision science, contributing to the interdisciplinary nature of the conference.

This book constitutes the proceedings of the Second Decision Science Alliance International Summer Conference, DSA ISC 2024, held in Valencia, Spain, in June 2024.The 33 full papers and 38 short papers included in this book were carefully reviewed and selected from 101 submissions.At the core of DSA ISC’24 are in-depth discussions and analyses across a spectrum of technological domains. Notably, experts shared their knowledge on areas such as Artificial Intelligence & Machine Learning, Mathematical Optimization, Operational Research & Management Science, Statistics, Simulation, and Decision Processes Analysis. Each of these areas represents a key aspect of decision science, contributing to the interdisciplinary nature of the conference.

This book constitutes the refereed post-conference proceedings of the 16th EAI International Conference on Simulation Tools and Techniques, SIMUTools 2024, held in Bratislava, Slovakia, in December 2024. The 26 full papers included in this book were carefully reviewed and selected from 63 submissions.

This book constitutes the revised selected papers from the International SpainTech-BAI 2025 Workshops held in Madrid, Terrassa, Pamplona, Benicassim, Spain, during March 19-20, 2025, May 14-15, 2025, September 25-26, 2025, and October 28-29, 2025.The 24 full papers included in this volume were carefully reviewed and selected from 31 invited submissions from 91 extended abstracts . They provide a view of recent advances in AI, optimization, data analytics, and applied technology, and serve as a useful reference for both research and practical implementation in Spain and Europe.

E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners’ performance in distributed learning environments.The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others.Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity.

Technology-Enhanced Systems and Tools for Collaborative Learning Scaffolding is a major research theme in CSCL and CSCW research community. This book presents up-to-date research approaches for developing technology-enhanced systems and tools to support functional online collaborative learning and work settings. It comprises a variety of research topics that span from the study of frameworks and infrastructures that foster collaborative learning and work through the application of different methods (distributed e-learning repositories, content creation and customization, social networks, collaborative ontologies building, and educational games) to the use of personalization and adaptation techniques to support the development of more powerful e-collaboration settings, including methodologies and tools for analyzing students' interactions with the aim to increase students' collaborative behaviors, performance and group organization. Researchers will find in this book the latest trends in these research topics, which gives them the opportunity to deepen further on the above issues and to extend their knowledge to other areas. Academics will find practical insights on how to use conceptual and experimental approaches in their daily tasks. Developers from CSCL community can be inspired and put in practice the proposed models and evaluate them for the specific purposes of their own work and context.

E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners’ performance in distributed learning environments.The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others.Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity.