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

Contributor(s): Hu, Bin [editor.] | López-Ibáñez, Manuel [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Theoretical Computer Science and General Issues: 10197Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: XII, 249 p. 46 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319554532.Subject(s): Numerical analysis | Algorithms | Computer science -- Mathematics | Discrete mathematics | Computer science | Artificial intelligence | Numerical Analysis | Algorithms | Discrete Mathematics in Computer Science | Theory of Computation | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 518 Online resources: Click here to access online
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 .
In: Springer Nature eBookSummary: 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 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 .

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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