Evolutionary Computation In Scheduling

Evolutionary Computation In Scheduling Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Evolutionary Computation In Scheduling book. This book definitely worth reading, it is an incredibly well-written.

Evolutionary Computation in Scheduling

Amir H. Gandomi,Ali Emrouznejad,Mo M. Jamshidi,Kalyanmoy Deb,Iman Rahimi
Evolutionary Computation in Scheduling Book PDF

Author : Amir H. Gandomi,Ali Emrouznejad,Mo M. Jamshidi,Kalyanmoy Deb,Iman Rahimi
Publisher : John Wiley & Sons
Page : 368 pages
File Size : 49,8 Mb
Release : 2020-05-19
Category : Mathematics
ISBN : 9781119573845

Get Book

Evolutionary Computation in Scheduling by Amir H. Gandomi,Ali Emrouznejad,Mo M. Jamshidi,Kalyanmoy Deb,Iman Rahimi Pdf

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 Search and the Job Shop

Dirk C. Mattfeld
Evolutionary Search and the Job Shop Book PDF

Author : Dirk C. Mattfeld
Publisher : Springer Science & Business Media
Page : 162 pages
File Size : 45,8 Mb
Release : 2013-04-17
Category : Business & Economics
ISBN : 9783662117125

Get Book

Evolutionary Search and the Job Shop by Dirk C. Mattfeld Pdf

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 Scheduling

Keshav Dahal,Kay Chen Tan,Peter I. Cowling
Evolutionary Scheduling Book PDF

Author : Keshav Dahal,Kay Chen Tan,Peter I. Cowling
Publisher : Springer Science & Business Media
Page : 631 pages
File Size : 46,5 Mb
Release : 2007-02-15
Category : Computers
ISBN : 9783540485827

Get Book

Evolutionary Scheduling by Keshav Dahal,Kay Chen Tan,Peter I. Cowling Pdf

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

Keshav Dahal,Kay Chen Tan,Peter I. Cowling
Evolutionary Scheduling Book PDF

Author : Keshav Dahal,Kay Chen Tan,Peter I. Cowling
Publisher : Springer
Page : 628 pages
File Size : 55,8 Mb
Release : 2007-04-25
Category : Computers
ISBN : 9783540485841

Get Book

Evolutionary Scheduling by Keshav Dahal,Kay Chen Tan,Peter I. Cowling Pdf

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.

OmeGA

Dimitri Knjazew
OmeGA Book PDF

Author : Dimitri Knjazew
Publisher : Springer Science & Business Media
Page : 165 pages
File Size : 46,7 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461508076

Get Book

OmeGA by Dimitri Knjazew Pdf

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.

Genetic Programming for Production Scheduling

Fangfang Zhang,Su Nguyen,Yi Mei,Mengjie Zhang
Genetic Programming for Production Scheduling Book PDF

Author : Fangfang Zhang,Su Nguyen,Yi Mei,Mengjie Zhang
Publisher : Springer Nature
Page : 357 pages
File Size : 43,7 Mb
Release : 2021-11-12
Category : Computers
ISBN : 9789811648595

Get Book

Genetic Programming for Production Scheduling by Fangfang Zhang,Su Nguyen,Yi Mei,Mengjie Zhang Pdf

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 Computation in Scheduling

Amir H. Gandomi,Ali Emrouznejad,Mo M. Jamshidi,Kalyanmoy Deb,Iman Rahimi
Evolutionary Computation in Scheduling Book PDF

Author : Amir H. Gandomi,Ali Emrouznejad,Mo M. Jamshidi,Kalyanmoy Deb,Iman Rahimi
Publisher : John Wiley & Sons
Page : 368 pages
File Size : 51,8 Mb
Release : 2020-04-29
Category : Mathematics
ISBN : 9781119573869

Get Book

Evolutionary Computation in Scheduling by Amir H. Gandomi,Ali Emrouznejad,Mo M. Jamshidi,Kalyanmoy Deb,Iman Rahimi Pdf

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 and Memetic Computing for Project Portfolio Selection and Scheduling

Kyle Robert Harrison,Saber Elsayed,Ivan Leonidovich Garanovich,Terence Weir,Sharon G. Boswell,Ruhul Amin Sarker
Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling Book PDF

Author : Kyle Robert Harrison,Saber Elsayed,Ivan Leonidovich Garanovich,Terence Weir,Sharon G. Boswell,Ruhul Amin Sarker
Publisher : Springer Nature
Page : 218 pages
File Size : 43,9 Mb
Release : 2021-11-13
Category : Technology & Engineering
ISBN : 9783030883157

Get Book

Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling by Kyle Robert Harrison,Saber Elsayed,Ivan Leonidovich Garanovich,Terence Weir,Sharon G. Boswell,Ruhul Amin Sarker Pdf

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.

Applications of Evolutionary Computing

Stefano Cagnoni,Jens Gottlieb,Emma Hart,Martin Middendorf,Günther R. Raidl
Applications of Evolutionary Computing Book PDF

Author : Stefano Cagnoni,Jens Gottlieb,Emma Hart,Martin Middendorf,Günther R. Raidl
Publisher : Springer
Page : 346 pages
File Size : 51,5 Mb
Release : 2003-07-31
Category : Computers
ISBN : 9783540460046

Get Book

Applications of Evolutionary Computing by Stefano Cagnoni,Jens Gottlieb,Emma Hart,Martin Middendorf,Günther R. Raidl Pdf

This book constitutes the refereed proceedings of three workshops on the application of evolutionary programming and algorithms in various domains; these workshops were held in conjunction with the 5th European Conference on Genetic Programming, EuroGP 2002, in Kinsale, Ireland, in April 2002. The 33 revised full papers presented were carefully reviewed and selected by the respective program committees. In accordance with the three workshops EvoCOP, EvoIASP, and EvoSTIM/EvoPLAN, the papers are organized in topical sections on combinatorial optimization problems; image analysis and signal processing; and scheduling, timetabling, and AI planning.

Evolutionary Algorithms in Engineering Applications

Dipankar Dasgupta,Zbigniew Michalewicz
Evolutionary Algorithms in Engineering Applications Book PDF

Author : Dipankar Dasgupta,Zbigniew Michalewicz
Publisher : Springer Science & Business Media
Page : 561 pages
File Size : 47,9 Mb
Release : 2013-06-29
Category : Computers
ISBN : 9783662034231

Get Book

Evolutionary Algorithms in Engineering Applications by Dipankar Dasgupta,Zbigniew Michalewicz Pdf

Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering. It will be useful for engineers, designers, developers, and researchers in any scientific discipline interested in the applications of evolutionary algorithms. The volume consists of five parts, each with four or five chapters. The topics are chosen to emphasize application areas in different fields of engineering. Each chapter can be used for self-study or as a reference by practitioners to help them apply evolutionary algorithms to problems in their engineering domains.

Evolutionary Computation

D. Dumitrescu,Beatrice Lazzerini,Lakhmi C. Jain,A. Dumitrescu
Evolutionary Computation Book PDF

Author : D. Dumitrescu,Beatrice Lazzerini,Lakhmi C. Jain,A. Dumitrescu
Publisher : CRC Press
Page : 424 pages
File Size : 45,5 Mb
Release : 2000-06-22
Category : Computers
ISBN : 0849305888

Get Book

Evolutionary Computation by D. Dumitrescu,Beatrice Lazzerini,Lakhmi C. Jain,A. Dumitrescu Pdf

Rapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving. Decision making, neural networks, pattern recognition, complex optimization/search tasks, scheduling, control, automated programming, and cellular automata applications all rely on evolutionary computation. Evolutionary Computation presents the basic principles of evolutionary computing: genetic algorithms, evolution strategies, evolutionary programming, genetic programming, learning classifier systems, population models, and applications. It includes detailed coverage of binary and real encoding, including selection, crossover, and mutation, and discusses the (m+l) and (m,l) evolution strategy principles. The focus then shifts to applications: decision strategy selection, training and design of neural networks, several approaches to pattern recognition, cellular automata, applications of genetic programming, and more.

Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation

Samuelson Hong, Wei-Chiang
Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation Book PDF

Author : Samuelson Hong, Wei-Chiang
Publisher : IGI Global
Page : 357 pages
File Size : 48,7 Mb
Release : 2013-03-31
Category : Computers
ISBN : 9781466636293

Get Book

Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation by Samuelson Hong, Wei-Chiang Pdf

Evolutionary computation has emerged as a major topic in the scientific community as many of its techniques have successfully been applied to solve problems in a wide variety of fields. Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation provides comprehensive research on emerging theories and its aspects on intelligent computation. Particularly focusing on breaking trends in evolutionary computing, algorithms, and programming, this publication serves to support professionals, government employees, policy and decision makers, as well as students in this scientific field.

Evolutionary Computation in Combinatorial Optimization

Martin Middendorf,Christian Blum
Evolutionary Computation in Combinatorial Optimization Book PDF

Author : Martin Middendorf,Christian Blum
Publisher : Springer
Page : 275 pages
File Size : 45,9 Mb
Release : 2013-03-12
Category : Computers
ISBN : 9783642371981

Get Book

Evolutionary Computation in Combinatorial Optimization by Martin Middendorf,Christian Blum Pdf

This book constitutes the refereed proceedings of the 13th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoBIO, EvoMUSART, and EvoApplications. The 23 revised full papers presented were carefully reviewed and selected from 50 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economic, and scientific domains. Prominent examples of metaheuristics are ant colony optimization, evolutionary algorithms, greedy randomized adaptive search procedures, iterated local search, simulated annealing, tabu search, and variable neighborhood search. Applications include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the travelling salesman problem, packing and cutting, satisfiability, and general mixed integer programming.

Massively Parallel Evolutionary Computation on GPGPUs

Shigeyoshi Tsutsui,Pierre Collet
Massively Parallel Evolutionary Computation on GPGPUs Book PDF

Author : Shigeyoshi Tsutsui,Pierre Collet
Publisher : Springer Science & Business Media
Page : 454 pages
File Size : 50,9 Mb
Release : 2013-12-05
Category : Computers
ISBN : 9783642379598

Get Book

Massively Parallel Evolutionary Computation on GPGPUs by Shigeyoshi Tsutsui,Pierre Collet Pdf

Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in domains such as scheduling, engineering, bioinformatics, and finance. Such applications demand acceptable solutions with high-speed execution using finite computational resources. Therefore, there have been many attempts to develop platforms for running parallel EAs using multicore machines, massively parallel cluster machines, or grid computing environments. Recent advances in general-purpose computing on graphics processing units (GPGPU) have opened up this possibility for parallel EAs, and this is the first book dedicated to this exciting development. The three chapters of Part I are tutorials, representing a comprehensive introduction to the approach, explaining the characteristics of the hardware used, and presenting a representative project to develop a platform for automatic parallelization of evolutionary computing (EC) on GPGPUs. The 10 chapters in Part II focus on how to consider key EC approaches in the light of this advanced computational technique, in particular addressing generic local search, tabu search, genetic algorithms, differential evolution, swarm optimization, ant colony optimization, systolic genetic search, genetic programming, and multiobjective optimization. The 6 chapters in Part III present successful results from real-world problems in data mining, bioinformatics, drug discovery, crystallography, artificial chemistries, and sudoku. Although the parallelism of EAs is suited to the single-instruction multiple-data (SIMD)-based GPU, there are many issues to be resolved in design and implementation, and a key feature of the contributions is the practical engineering advice offered. This book will be of value to researchers, practitioners, and graduate students in the areas of evolutionary computation and scientific computing.

Introduction to Evolutionary Computing

Agoston E. Eiben,J.E. Smith
Introduction to Evolutionary Computing Book PDF

Author : Agoston E. Eiben,J.E. Smith
Publisher : Springer Science & Business Media
Page : 307 pages
File Size : 49,8 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9783662050941

Get Book

Introduction to Evolutionary Computing by Agoston E. Eiben,J.E. Smith Pdf

The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.