Evolutionary scheduling
Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are ofte...
Tallennettuna:
| Päätekijä: | |
|---|---|
| Muut tekijät: | , , |
| Aineistotyyppi: | Livre numérique |
| Kieli: | Anglais |
| Julkaistu: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Painos: | 1st ed. 2007. |
| Sarja: | Studies in Computational Intelligence
49 |
| Linkit: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Huomautus: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Evolutionary scheduling, edited by Keshav Dahal, Kay Chen Tan and Peter I. Cowling, Berlin, Springer, 2007, xi, 628 p., Studies in computational intelligence, 978-3-540-48582-7 • Evolutionary Scheduling, Texte imprimé, 9783540832461 • Evolutionary Scheduling, Texte imprimé, 9783642080173 • Evolutionary scheduling, edited by Keshav Dahal, Kay Chen Tan and Peter I. Cowling, Berlin, Springer, 2007, xi, 628 p., Studies in computational intelligence, 978-3-540-48582-7 |
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| 041 | 0 | |a eng | |
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| 100 | 1 | |a Dahal, Keshav. | |
| 245 | 1 | 0 | |a Evolutionary scheduling |c edited by Keshav P. Dahal, Kay Chen Tan, Peter I. Cowling. |
| 250 | |a 1st ed. 2007. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Computational Intelligence |v 49 |x 1860-9503 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a 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 for an Inventory Location Problem | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computational techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, are derived from biologically inspired concepts and are well-suited to solve scheduling problems since they are highly scalable and flexible in terms of handling constraints and multiple objectives. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling, and 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. The intended readers of this book are engineers, researchers, practitioners, senior undergraduates, and graduate students who are interested in the field of evolutionary scheduling | ||
| 700 | 1 | |a Tan, Kay Chen. |4 edt | |
| 700 | 1 | |a Cowling, Peter I. |4 edt | |
| 700 | 1 | |a Dahal, Keshav. |4 pbd | |
| 700 | 1 | |a Cowling, Peter Ivan, |d 19..- |4 pbd | |
| 700 | 1 | |a Tan, Kay Chen. |4 pbd | |
| 776 | 0 | |0 184665876 |t Evolutionary scheduling |f edited by Keshav Dahal, Kay Chen Tan and Peter I. Cowling |c Berlin |n Springer |d 2007 |p xi, 628 p. |s Studies in computational intelligence |z 978-3-540-48582-7 | |
| 776 | 0 | |t Evolutionary Scheduling |b Texte imprimé |z 9783540832461 | |
| 776 | 0 | |t Evolutionary Scheduling |b Texte imprimé |z 9783642080173 | |
| 776 | 0 | |0 184665876 |t Evolutionary scheduling |f edited by Keshav Dahal, Kay Chen Tan and Peter I. Cowling |c Berlin |n Springer |d 2007 |p xi, 628 p. |s Studies in computational intelligence |z 978-3-540-48582-7 | |
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| 997 | |0 939207 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/Autre ressource numérique/ | ||