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ISBN: 9783642080173

Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex… mais…

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Evolutionary Scheduling - Livro de bolso

2010, ISBN: 3642080170

[EAN: 9783642080173], Neubuch, [PU: Springer Berlin Heidelberg], COMPUTATIONALINTELLIGENCE EVOLUTION EVOLUTIONARYALGORITHMS FUZZY OPERATIONSRESEARCH ALGORITHM ARTIFICIALINTELLIGENCE EVOLU… mais…

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2010

ISBN: 9783642080173

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Evolutionary Scheduling - Livro de bolso

2007, ISBN: 3642080170

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Keshav Dahal; Kay Chen Tan; Peter I. Cowling:
Evolutionary Scheduling - Livro de bolso

2010, ISBN: 9783642080173

Buch, Softcover, Softcover reprint of hardcover 1st ed. 2007, [PU: Springer Berlin], Springer Berlin, 2010

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Evolutionary Scheduling
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9783642080173


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.

Dados detalhados do livro - Evolutionary Scheduling


EAN (ISBN-13): 9783642080173
ISBN (ISBN-10): 3642080170
Livro de capa dura
Livro de bolso
Ano de publicação: 2010
Editor/Editora: Springer Berlin
640 Páginas
Peso: 0,953 kg
Língua: eng/Englisch

Livro na base de dados desde 2012-02-22T08:13:18-02:00 (Sao Paulo)
Página de detalhes modificada pela última vez em 2023-01-26T18:51:02-03:00 (Sao Paulo)
Número ISBN/EAN: 9783642080173

Número ISBN - Ortografia alternativa:
3-642-08017-0, 978-3-642-08017-3
Ortografia alternativa e termos de pesquisa relacionados:
Autor do livro: peter chen
Título do livro: scheduling

Dados da editora

Autor: Keshav Dahal; Kay Chen Tan; Peter I. Cowling
Título: Studies in Computational Intelligence; Evolutionary Scheduling
Editora: Springer; Springer Berlin
628 Páginas
Ano de publicação: 2010-11-30
Berlin; Heidelberg; DE
Impresso / Feito em
Língua: Inglês
160,49 € (DE)
164,99 € (AT)
177,00 CHF (CH)
POD
XI, 628 p.

BC; Hardcover, Softcover / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Computational Intelligence; Evolution; Evolutionary Algorithms; Fuzzy; Operations Research; algorithm; artificial intelligence; evolutionary algorithm; evolutionary strategies; genetic algorithms; heuristics; intelligence; metaheuristic; optimization; programming; Artificial Intelligence; Mathematical and Computational Engineering Applications; Mathematik für Ingenieure; BB

Methodology.- Memetic Algorithms in Planning, Scheduling, and Timetabling.- Landscapes, Embedded Paths and Evolutionary Scheduling.- Classical and Non-Classical Models of Production Scheduling.- Scheduling of Flow-Shop, Job-Shop, and Combined Scheduling Problems using MOEAs with Fixed and Variable Length Chromosomes.- Designing Dispatching Rules to Minimize Total Tardiness.- A Robust Meta-Hyper-Heuristic Approach to Hybrid Flow-Shop Scheduling.- Hybrid Particle Swarm Optimizers in the Single Machine Scheduling Problem: An Experimental Study.- An Evolutionary Approach for Solving the Multi-Objective Job-Shop Scheduling Problem.- Timetabling.- Multi-Objective Evolutionary Algorithm for University Class Timetabling Problem.- Metaheuristics for University Course Timetabling.- Energy Applications.- Optimum Oil Production Planning using an Evolutionary Approach.- A Hybrid Evolutionary Algorithm for Service Restoration in Power Distribution Systems.- Particle Swarm Optimisation for Operational Planning: Unit Commitment and Economic Dispatch.- Evolutionary Generator Maintenance Scheduling in Power Systems.- Networks.- Evolvable Fuzzy Scheduling Scheme for Multiple-ChannelPacket Switching Network.- A Multi-Objective Evolutionary Algorithm for Channel Routing Problems.- Transport.- Simultaneous Planning and Scheduling for Multi-Autonomous Vehicles.- Scheduling Production and Distribution of Rapidly Perishable Materials with Hybrid GA's.- A Scenario-based Evolutionary Scheduling Approach for Assessing Future Supply Chain Fleet Capabilities.- Business.- Evolutionary Optimization of Business Process Designs.- Using a Large Set of Low Level Heuristics in a Hyperheuristic Approach to Personnel Scheduling.- A Genetic-Algorithm-Based Reconfigurable Scheduler.- Evolutionary Algorithm foran Inventory Location Problem.
Demonstrate the applicability of evolutionary computational techniques to solve scheduling problems

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