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{ "item_title" : "Evolutionary Computation in Combinatorial Optimization", "item_author" : [" Martin Middendorf", "Christian Blum "], "item_description" : "A Hyper-heuristic with a Round Robin Neighbourhood.- A Multiobjective Approach Based on the Law of Gravity and Mass Interactions for Optimizing Networks.- A Multi-objective Feature Selection Approach Based on Binary PSO and Rough Set Theory.- A New Crossover for Solving Constraint Satisfaction Problems.- A Population-Based Strategic Oscillation Algorithm for Linear Ordering Problem with Cumulative Costs.- A Study of Adaptive Perturbation Strategy for Iterated Local Search.- Adaptive MOEA/D for QoS-Based Web Service Composition.- An Analysis of Local Search for the Bi-objective Bidimensional Knapsack Problem.- An Artificial Immune System Based Approach for Solving the Nurse Re-rostering Problem.- Automatic Algorithm Selection for the Quadratic Assignment Problem Using Fitness Landscape Analysis.- Balancing Bicycle Sharing Systems: A Variable Neighborhood Search Approach.- Combinatorial Neighborhood Topology Particle Swarm Optimization Algorithm for the Vehicle Routing Problem.- Dynamic Evolutionary Membrane Algorithm in Dynamic Environments.- From Sequential to Parallel Local Search for SAT.- Generalizing Hyper-heuristics via Apprenticeship Learning.- High-Order Sequence Entropies for Measuring Population Diversity in the Traveling Salesman Problem.- Investigating Monte-Carlo Methods on the Weak Schur Problem.- Multi-objective AI Planning: Comparing Aggregation and Pareto Approaches.- Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape.- Single Line Train Scheduling with ACO.- Solving Clique Covering in Very Large Sparse Random Graphs by a Technique Based on k-Fixed Coloring Tabu Search.- Solving the Virtual Network Mapping Problem with Construction Heuristics, Local Search and Variable Neighborhood Descent.- The Generate-and-Solve Framework Revisited: Generating by Simulated Annealing.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/64/237/197/3642371973_b.jpg", "price_data" : { "retail_price" : "49.99", "online_price" : "49.99", "our_price" : "49.99", "club_price" : "49.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Evolutionary Computation in Combinatorial Optimization|Martin Middendorf

Evolutionary Computation in Combinatorial Optimization : 13th European Conference, Evocop 2013, Vienna, Austria, April 3-5, 2013, Proceedings

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Overview

A Hyper-heuristic with a Round Robin Neighbourhood.- A Multiobjective Approach Based on the Law of Gravity and Mass Interactions for Optimizing Networks.- A Multi-objective Feature Selection Approach Based on Binary PSO and Rough Set Theory.- A New Crossover for Solving Constraint Satisfaction Problems.- A Population-Based Strategic Oscillation Algorithm for Linear Ordering Problem with Cumulative Costs.- A Study of Adaptive Perturbation Strategy for Iterated Local Search.- Adaptive MOEA/D for QoS-Based Web Service Composition.- An Analysis of Local Search for the Bi-objective Bidimensional Knapsack Problem.- An Artificial Immune System Based Approach for Solving the Nurse Re-rostering Problem.- Automatic Algorithm Selection for the Quadratic Assignment Problem Using Fitness Landscape Analysis.- Balancing Bicycle Sharing Systems: A Variable Neighborhood Search Approach.- Combinatorial Neighborhood Topology Particle Swarm Optimization Algorithm for the Vehicle Routing Problem.- Dynamic Evolutionary Membrane Algorithm in Dynamic Environments.- From Sequential to Parallel Local Search for SAT.- Generalizing Hyper-heuristics via Apprenticeship Learning.- High-Order Sequence Entropies for Measuring Population Diversity in the Traveling Salesman Problem.- Investigating Monte-Carlo Methods on the Weak Schur Problem.- Multi-objective AI Planning: Comparing Aggregation and Pareto Approaches.- Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape.- Single Line Train Scheduling with ACO.- Solving Clique Covering in Very Large Sparse Random Graphs by a Technique Based on k-Fixed Coloring Tabu Search.- Solving the Virtual Network Mapping Problem with Construction Heuristics, Local Search and Variable Neighborhood Descent.- The Generate-and-Solve Framework Revisited: Generating by Simulated Annealing.

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Details

  • ISBN-13: 9783642371974
  • ISBN-10: 3642371973
  • Publisher: Springer
  • Publish Date: March 2013
  • Dimensions: 9.21 x 6.14 x 0.6 inches
  • Shipping Weight: 0.9 pounds
  • Page Count: 275

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