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|a Evolutionary Computation in Combinatorial Optimization
|h [electronic resource] :
|b 17th European Conference, EvoCOP 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings /
|c edited by Bin Hu, Manuel López-Ibáñez.
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| 250 |
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|a 1st ed. 2017.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2017.
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|a XII, 249 p. 46 illus.
|b online resource.
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|a Theoretical Computer Science and General Issues ;
|v 10197
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|a 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 Consideration of Soft Time Windows in a Large Neighborhood Search for the Districting and Routing Problem for Security Control -- Estimation of Distribution Algorithms for the Firefighter Problem -- LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows -- Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO -- Optimizing Charging Station Locations for Electric Car-Sharing Systems -- Selection of Auxiliary Objectives Using Landscape Features and Offline Learned Classifier -- Sparse, Continuous Policy Representations for Uniform Online Bin Packing via Regression of Interpolants -- The Weighted Independent Domination Problem: ILP Model and Algorithmic .
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|a 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 algorithms, beam search, ant colony optimization, hyper-heuristics and matheuristics. Applications include both traditional domains, such as knapsack problem, vehicle routing, scheduling problems and SAT; and newer domains such as the traveling thief problem, location planning for car-sharing systems and spacecraft trajectory optimization. Papers also study important concepts such as pseudo-backbones, phase transitions in local optima networks, and the analysis of operators. This wide range of topics makes the EvoCOP proceedings an important source for current research trends in combinatorial optimization.
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|a Numerical analysis.
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|a Algorithms.
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|a Computer science—Mathematics.
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|a Computers.
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|a Artificial intelligence.
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|a Numeric Computing.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I1701X
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|a Algorithm Analysis and Problem Complexity.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I16021
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| 650 |
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|a Discrete Mathematics in Computer Science.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I17028
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| 650 |
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|a Computation by Abstract Devices.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I16013
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|a Artificial Intelligence.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I21000
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| 700 |
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|a Hu, Bin.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a López-Ibáñez, Manuel.
|e editor.
|0 (orcid)0000-0001-9974-1295
|1 https://orcid.org/0000-0001-9974-1295
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 710 |
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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| 776 |
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|i Printed edition:
|z 9783319554525
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| 776 |
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|i Printed edition:
|z 9783319554549
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| 830 |
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|a Theoretical Computer Science and General Issues ;
|v 10197
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|u https://doi.org/10.1007/978-3-319-55453-2
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|a Computer Science (SpringerNature-11645)
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|a Computer Science (R0) (SpringerNature-43710)
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