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Evolutionary Computation in Combinatorial Optimization -

Evolutionary Computation in Combinatorial Optimization

17th European Conference, EvoCOP 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings
Buch | Softcover
XII, 249 Seiten
2017 | 1st ed. 2017
Springer International Publishing (Verlag)
978-3-319-55452-5 (ISBN)
CHF 74,85 inkl. MwSt
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.

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 

Erscheinungsdatum
Reihe/Serie Lecture Notes in Computer Science
Theoretical Computer Science and General Issues
Zusatzinfo XII, 249 p. 46 illus.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Schlagworte algorithms • ant colony optimization • Applications • combinatorial optimization • Computer Science • conference proceedings • Discrete Space Search • Estimation of Distribution Algorithms • evolutionary algorithms • Graph problem • hyper-heuristics • Informatics • Informatik • Linear Programming • Mathematical theory of computation • Matheuristics • memetic algorithm • Metaheuristics • Multi-Objective Optimization • numeric computing • Optimization Problems • particle swarm optimisation • Permutation problems • Quadratic assignment • Research • Routing • Search Methodologies • Vehicle Routing
ISBN-10 3-319-55452-2 / 3319554522
ISBN-13 978-3-319-55452-5 / 9783319554525
Zustand Neuware
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