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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.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Theoretical computer science and general issues 2512-2029 ; SL 1, 10197
- Theoretical Computer Science and General Issues, 2512-2029 ; 10197
- Language:
- English
- Subjects (All):
- Numerical analysis.
- Algorithms.
- Computer science-Mathematics.
- Discrete mathematics.
- Computer science.
- Artificial intelligence.
- Numerical Analysis.
- Discrete Mathematics in Computer Science.
- Theory of Computation.
- Artificial Intelligence.
- Local Subjects:
- Numerical Analysis.
- Algorithms.
- Discrete Mathematics in Computer Science.
- Theory of Computation.
- Artificial Intelligence.
- Physical Description:
- 1 online resource (XII, 249 pages) : 46 illustrations
- Edition:
- 1st ed. 2017.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2017.
- System Details:
- text file PDF
- 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 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.
- 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 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 .
- Other Format:
- Printed edition:
- ISBN:
- 978-3-319-55453-2
- 9783319554532
- Access Restriction:
- Restricted for use by site license.
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