Javier Faulin – författare

Sustainable Transportation and Smart Logistics: Decision-Making Models and Solutions provides deterministic and probabilistic models for transportation logistics problem-solving and decision-making. The book presents an overview of the intersections between sustainability, transportation, and logistics, and delves into the current problems associated with the implementation of sustainable transportation and smart logistics in urban settings. It also offers models for addressing complex structural problems and procedures for estimating transportation externalities such as environmental and social impacts, both in industrial and government arenas, as well as decision-making models from operational, tactical, and strategic management perspectives. Sustainable Transportation and Smart Logistics also covers best practices for practical corporate policy implementation, making it a comprehensive and vital resource for researchers, graduate students, practitioners, and policy makers in transportation, logistics, urban planning, economics, engineering, and environmental science.

Examines various modes of transportation Includes mathematical models for decision-making in a wide variety of situations Presents public transportation and smart cities use cases

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.