Evolutionary Computation in Combinatorial Optimization : 17th European Conference, EvoCOP 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings / edited by Bin Hu, Manuel López-Ibáñez

Mitwirkende(r):

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: SpringerLink Bücher | Lecture notes in computer science ; 10197Verlag: Cham : Springer, 2017Beschreibung: Online-Ressource (XII, 249 p. 46 illus, online resource)ISBN:

9783319554532

Schlagwörter:

Andere physische Formen: 9783319554525 | Erscheint auch als: 978-3-319-55452-5 Druck-AusgabeMSC: MSC: *68-06 | 68T20 | 90C27 | 90C59 | 00B25LOC-Klassifikation:

QA297-299.4

DOI: DOI: 10.1007/978-3-319-55453-2Online-Ressourcen:

Zusammenfassung: 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 optimizationZusammenfassung: 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 AlgorithmicPPN: PPN: 1658303911Package identifier: Produktsigel: ZDB-2-LNC | ZDB-2-SCS | ZDB-2-SXCS | ZDB-2-SEB | ZDB-2-SEB

Exemplare ( 0 )

Dieser Titel hat keine Exemplare