A multi-level simulation-based optimization framework for IoT-enabled elderly care systems
TL;DR: In this article, a multi-level framework that combines a simulation and optimization approach is proposed to evaluate the performance of complex systems triggered by real-time IoT-fed "service requests".
About: This article is published in Simulation Modelling Practice and Theory.The article was published on 2022-01-01. It has received 1 citations till now. The article focuses on the topics: Service (business) & Computer science.
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TL;DR: In this article , a discrete event simulation (DES) model is developed to capture the randomness and complexity of the entire emergency healthcare chain, including an Emergency Medical Service (EMS), an Emergency Department (ED), and an Observation Unit (OU).
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Book•
01 Jan 2020TL;DR: In this article, the authors present a comprehensive introduction to the theory and practice of artificial intelligence for modern applications, including game playing, planning and acting, and reinforcement learning with neural networks.
Abstract: The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For computer professionals, linguists, and cognitive scientists interested in artificial intelligence.
16,983 citations
Book•
01 Jan 1998
TL;DR: In this article, the authors introduce the subject of simulation using examples from Arena and are designed for the introductory simulation course offered in industrial engineering and business departments Simulation with Arena is the only book to cover the Arena product and it is accompanied by an Arena CD.
Abstract: From the Publisher:
Arena is the world's most effective simulation technology for modeling systems in manufacturing,transportation,logistics,warehousing,and business processing This highly anticipated text introduces the subject of simulation using examples from Arena and is designed for the introductory simulation course offered in industrial engineering and business departments Simulation with Arena is the only book to cover the Arena product and it is accompanied by an Arena CD
2,169 citations
TL;DR: The Handbook now includes updated chapters on the best known metaheuristics, including simulated annealing, tabu search, variable neighborhood search, scatter search and path relinking, genetic algorithms, memetic algorithms, genetic programming, ant colony optimization, and multi-start methods.
Abstract: The first edition of the Handbook of Metaheuristics was published in 2003 under the editorship of Fred Glover and Gary A. Kochenberger. Given the numerous developments observed in the field of metaheuristics in recent years, it appeared that the time was ripe for a second edition of the Handbook. When Glover and Kochenberger were unable to prepare this second edition, they suggested that Michel Gendreau and Jean-Yves Potvin should take over the editorship, and so this important new edition is now available. Through its 21 chapters, this second edition is designed to provide a broad coverage of the concepts, implementations and applications in this important field of optimization. Original contributors either revised or updated their work, or provided entirely new chapters. The Handbook now includes updated chapters on the best known metaheuristics, including simulated annealing, tabu search, variable neighborhood search, scatter search and path relinking, genetic algorithms, memetic algorithms, genetic programming, ant colony optimization, multi-start methods, greedy randomized adaptive search procedure, guided local search, hyper-heuristics and parallel metaheuristics. It also contains three new chapters on large neighborhood search, artificial immune systems and hybrid metaheuristics. The last four chapters are devoted to more general issues related to the field of metaheuristics, namely reactive search, stochastic search, fitness landscape analysis and performance comparison.
1,208 citations
Book•
18 Jan 2000
TL;DR: Part I: Basics.
Abstract: Part I: Basics. Introduction to Systems Modeling Concepts. Framework for Modeling and Simulation. Modeling Formalisms and Their Simulators. Introduction to Discrete Event System Specifications (DEVS). Hierarchy of System Specifications. Part II: Modeling Formalisms and Simulation Algorithms. Basic Formalisms: DEVS, DTSS, DESS. Basic Formalisms: Coupled Multicomponent Systems. Simulators for Basic Formalisms. Multiformalism Modeling and Simulation. DEVS-Based Extended Formalisms. Parallel and Distributed Discrete Event Simulation. Part III: System Morphisms: Abstraction, Representation, Approximation. Hierarchy of System Morphisms. Abstraction: Constructing Model Families. Verification, Validation, Approximate Morphisms: Living with Error. DEVS and DEVS-like Systems: Universality and Uniqueness. DEVS Representation of Systems. Part IV: System Design and Modeling and Simulation Environments. DEVS-Based Design Methodology. System Entity Structure/Model Base Framework. Collaboration and the Future.
1,169 citations