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Book Synopsis

.- A Runtime Analysis of the Multi-Valued Compact Genetic Algorithm on Generalized LeadingOnes.
.- Evolutionary Anytime Algorithms.
.- Studies on Survival Strategies to Protect Expert Knowledge in Evolutionary Algorithms for Interactive Role Mining.
.- Diversification through Candidate Sampling for a Non-Iterated Lin-Kernighan-Helsgaun Algorithm.
.- Instance Space Analysis and Algorithm Selection for a Parallel Batch Scheduling Problem.
.- Meta-learning of Univariate Estimation-of-Distribution Algorithms for Pseudo-Boolean Problems.
.- A Selective Vehicle Routing Problem for the Bloodmobile System.
.- A Genetic Approach to the Operational Freight-on-Transit problem.
.- LON/D — Sub-problem Landscape Analysis in Decomposition-based Multi-objective Optimization.
.- Visualizing Pseudo-Boolean Functions: Feature Selection and Regularization for Machine Learning.
.- Mixed-Binary Problems Optimized with Fast Discrete Solver.
.- Feature-based Evolutionary Diversity Optimization of Discriminating Instances for Chance-constrained Optimization Problems.
.- Adaptive neighborhood search based on landscape learning: a TSP study.
.- Healthcare Facility Location Problem and Fitness Landscape Analysis.
.- Generating (Semi-)Active Schedules for Dynamic Multi-mode Project Scheduling Using Genetic Programming Hyper-heuristics.
.- Price-and-branch Heuristic for Vector Bin Packing.

Evolutionary Computation in Combinatorial Optimization

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    A Paperback by Martin S. Krejca

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      View other formats and editions of Evolutionary Computation in Combinatorial Optimization by Martin S. Krejca

      Publisher: Springer
      Publication Date: Publication Date: 21/04/2025
      ISBN13: 9783031868481, 978-3031868481
      ISBN10:
      Also in:
      Computing Maths for computer scientists

      Description

      Book Synopsis

      .- A Runtime Analysis of the Multi-Valued Compact Genetic Algorithm on Generalized LeadingOnes.
      .- Evolutionary Anytime Algorithms.
      .- Studies on Survival Strategies to Protect Expert Knowledge in Evolutionary Algorithms for Interactive Role Mining.
      .- Diversification through Candidate Sampling for a Non-Iterated Lin-Kernighan-Helsgaun Algorithm.
      .- Instance Space Analysis and Algorithm Selection for a Parallel Batch Scheduling Problem.
      .- Meta-learning of Univariate Estimation-of-Distribution Algorithms for Pseudo-Boolean Problems.
      .- A Selective Vehicle Routing Problem for the Bloodmobile System.
      .- A Genetic Approach to the Operational Freight-on-Transit problem.
      .- LON/D — Sub-problem Landscape Analysis in Decomposition-based Multi-objective Optimization.
      .- Visualizing Pseudo-Boolean Functions: Feature Selection and Regularization for Machine Learning.
      .- Mixed-Binary Problems Optimized with Fast Discrete Solver.
      .- Feature-based Evolutionary Diversity Optimization of Discriminating Instances for Chance-constrained Optimization Problems.
      .- Adaptive neighborhood search based on landscape learning: a TSP study.
      .- Healthcare Facility Location Problem and Fitness Landscape Analysis.
      .- Generating (Semi-)Active Schedules for Dynamic Multi-mode Project Scheduling Using Genetic Programming Hyper-heuristics.
      .- Price-and-branch Heuristic for Vector Bin Packing.

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