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Evolutionary Computation in Combinatorial Optimization : 17th European Conference, EvoCOP 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings /

This book constitutes the refereed proceedings of the 17th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo*2017 events EuroGP, EvoMUSART and EvoApplications. The 16 revised full pap...

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Bibliographic Details
Corporate Authors: SpringerLink Online service
Group Author: Hu, Bin; L pez-Ib ez, Manuel
Published: Springer International Publishing : Imprint: Springer,
Publisher Address: Cham :
Publication Dates: 2017.
Literature type: eBook
Language: English
Series: Lecture Notes in Computer Science, 10197
Subjects:
Computer science
Computers
Algorithms
Numerical analysis
Computer science > Mathematics
Artificial intelligence
Numeric Computing
Algorithm Analysis and Problem Complexity
Discrete Mathematics in Computer Science
Computation by Abstract Devices
Artificial Intelligence incl. Robotics
Online Access: http://dx.doi.org/10.1007/978-3-319-55453-2
Summary: This book constitutes the refereed proceedings of the 17th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo*2017 events EuroGP, EvoMUSART and EvoApplications. The 16 revised full papers presented were carefully reviewed and selected from 39 submissions. The papers cover both empirical and theoretical studies on a wide range of academic and real-world applications. The methods include evolutionary and memetic algorithms, large neighborhood search, estimation of distribution al
Carrier Form: 1 online resource (XII, 249 pages): illustrations.
ISBN: 9783319554532
Index Number: QA297
CLC: O241
Contents: A Computational Study of Neighborhood Operators for Job-shop Scheduling Problems with Regular Objectives -- A Genetic Algorithm for Multi-Component Optimization Problems: the Case of the Travelling Thief Problem -- A Hybrid Feature Selection Algorithm Based on Large Neighborhood Search -- A Memetic Algorithm to Maximise the Employee Substitutability in Personnel Shift Scheduling -- Construct, Merge, Solve and Adapt versus Large Neighborhood Search for Solving the Multi-Dimensional Knapsack Problem: Which One Works Better When -- Decomposing SAT Instances with Pseudo Backbones -- Efficient Co

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