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Evolutionary Scheduling

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Evolutionary Computation In Scheduling

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Author : Amir H. Gandomi
language : en
Publisher: John Wiley & Sons
Release Date : 2020-05-19

Evolutionary Computation In Scheduling written by Amir H. Gandomi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-19 with Mathematics categories.

Presents current developments in the field of evolutionary scheduling and demonstrates the applicability of evolutionary computational techniques to solving scheduling problems This book provides insight into the use of evolutionary computations (EC) in real-world scheduling, showing readers how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. It offers a spectrum of real-world optimization problems, including applications of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. It also features problems with different degrees of complexity, practical requirements, user constraints, and MOEC solution approaches. Evolutionary Computation in Scheduling starts with a chapter on scientometric analysis to analyze scientific literature in evolutionary computation in scheduling. It then examines the role and impacts of ant colony optimization (ACO) in job shop scheduling problems, before presenting the application of the ACO algorithm in healthcare scheduling. Other chapters explore task scheduling in heterogeneous computing systems and truck scheduling using swarm intelligence, application of sub-population scheduling algorithm in multi-population evolutionary dynamic optimization, task scheduling in cloud environments, scheduling of robotic disassembly in remanufacturing using the bees algorithm, and more. This book: Provides a representative sampling of real-world problems currently being tackled by practitioners Examines a variety of single-, multi-, and many-objective problems that have been solved using evolutionary computations, including evolutionary algorithms and swarm intelligence Consists of four main parts: Introduction to Scheduling Problems, Computational Issues in Scheduling Problems, Evolutionary Computation, and Evolutionary Computations for Scheduling Problems Evolutionary Computation in Scheduling is ideal for engineers in industries, research scholars, advanced undergraduates and graduate students, and faculty teaching and conducting research in Operations Research and Industrial Engineering.

Evolutionary Scheduling

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Author : Keshav Dahal
language : en
Publisher: Springer
Release Date : 2007-04-25

Evolutionary Scheduling written by Keshav Dahal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-25 with Computers categories.

Evolutionary scheduling is a vital research domain at the interface of artificial intelligence and operational research. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling. It demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems.

Evolutionary Scheduling

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Author : Keshav Dahal
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-02-15

Evolutionary Scheduling written by Keshav Dahal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-02-15 with Computers categories.

Genetic Programming For Production Scheduling

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Author : Fangfang Zhang
language : en
Publisher: Springer Nature
Release Date : 2021-11-12

Genetic Programming For Production Scheduling written by Fangfang Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-12 with Computers categories.

This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling. The book is divided into six parts. In Part I, it provides an introduction to production scheduling, existing solution methods, and the GP approach to production scheduling. Characteristics of production environments, problem formulations, an abstract GP framework for production scheduling, and evaluation criteria are also presented. Part II shows various ways that GP can be employed to solve static production scheduling problems and their connections with conventional operation research methods. In turn, Part III shows how to design GP algorithms for dynamic production scheduling problems and describes advanced techniques for enhancing GP’s performance, including feature selection, surrogate modeling, and specialized genetic operators. In Part IV, the book addresses how to use heuristics to deal with multiple, potentially conflicting objectives in production scheduling problems, and presents an advanced multi-objective approach with cooperative coevolution techniques or multi-tree representations. Part V demonstrates how to use multitask learning techniques in the hyper-heuristics space for production scheduling. It also shows how surrogate techniques and assisted task selection strategies can benefit multitask learning with GP for learning heuristics in the context of production scheduling. Part VI rounds out the text with an outlook on the future. Given its scope, the book benefits scientists, engineers, researchers, practitioners, postgraduates, and undergraduates in the areas of machine learning, artificial intelligence, evolutionary computation, operations research, and industrial engineering.

Evolutionary Search And The Job Shop

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Author : Dirk C. Mattfeld
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17

Evolutionary Search And The Job Shop written by Dirk C. Mattfeld and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Business & Economics categories.

Production scheduling dictates highly constrained mathematical models with complex and often contradicting objectives. Evolutionary algorithms can be formulated almost independently of the detailed shaping of the problems under consideration. As one would expect, a weak formulation of the problem in the algorithm comes along with a quite inefficient search. This book discusses the suitability of genetic algorithms for production scheduling and presents an approach which produces results comparable with those of more tailored optimization techniques.

Evolutionary And Memetic Computing For Project Portfolio Selection And Scheduling

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Author : Kyle Robert Harrison
language : en
Publisher: Springer Nature
Release Date : 2021-11-13

Evolutionary And Memetic Computing For Project Portfolio Selection And Scheduling written by Kyle Robert Harrison and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-13 with Technology & Engineering categories.

This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times. It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes. This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing.

Evolutionary Computation In Scheduling

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Author : Amir H. Gandomi
language : en
Publisher: John Wiley & Sons
Release Date : 2020-04-09

Omega

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Author : Dimitri Knjazew
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Omega written by Dimitri Knjazew and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

OmeGA: A Competent Genetic Algorithm for Solving Permutation and Scheduling Problems addresses two increasingly important areas in GA implementation and practice. OmeGA, or the ordering messy genetic algorithm, combines some of the latest in competent GA technology to solve scheduling and other permutation problems. Competent GAs are those designed for principled solutions of hard problems, quickly, reliably, and accurately. Permutation and scheduling problems are difficult combinatorial optimization problems with commercial import across a variety of industries. This book approaches both subjects systematically and clearly. The first part of the book presents the clearest description of messy GAs written to date along with an innovative adaptation of the method to ordering problems. The second part of the book investigates the algorithm on boundedly difficult test functions, showing principled scale up as problems become harder and longer. Finally, the book applies the algorithm to a test function drawn from the literature of scheduling.

Evolutionary Computation In Combinatorial Optimization

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Author : Gabriela Ochoa
language : en
Publisher: Springer
Release Date : 2015-03-14

Evolutionary Computation In Combinatorial Optimization written by Gabriela Ochoa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-14 with Computers categories.

This book constitutes the refereed proceedings of the 15th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2015, held in Copenhagen, Denmark, in April 2015, co-located with the Evo*2015 events EuroGP, EvoMUSART and EvoApplications. The 19 revised full papers presented were carefully reviewed and selected from 46 submissions. The papers cover methodology, applications and theoretical studies. The methods included evolutionary and memetic (hybrid) algorithms, iterated local search, variable neighbourhood search, ant colony optimization, artificial immune systems, hyper-heuristics and other adaptive approaches. The applications include both traditional domains, such as graph coloring, knapsack, vehicle routing, job-shop scheduling, the p-median and the orienteering problems; and new(er) domains such as designing deep recurrent neural networks, detecting network community structure, lock scheduling of ships, cloud resource management, the fire-fighter problem and AI planning. The theoretical studies involved approximation ratio, runtime and black-box complexity analyses.

Genetic Algorithms And Application In Examination Scheduling

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Author : Dang Xuan Tho
language : en
Publisher: GRIN Verlag
Release Date : 2010-06

Genetic Algorithms And Application In Examination Scheduling written by Dang Xuan Tho and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06 with Computers categories.

Research Paper (undergraduate) from the year 2009 in the subject Computer Science - Applied, language: English, abstract: Abstract In this thesis, we present an introduction about genetic algorithms (GAs). Genetic algorithms are not too hard to program or understand, since they are biologically based. This thesis also shows scheduling problems, expecially examination scheduling problems. We provide a way that can be easily used to apply the evolutionary principle to the problem solutions. Furthermore, these are the program's applications in reality as well as in science. Keyword: Genetic Algorithms, Scheduling Problems, Examination Scheduling Problems.

Evolutionary Scheduling

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