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

This book constitutes the refereed proceedings of the 13th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoBIO, EvoMUSART, and EvoApplications. The 23 revised full papers presented were carefully reviewed and selected from 50 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economic, and scientific domains. Prominent examples of metaheuristics are ant colony optimization, evolutionary algorithms, greedy randomized adaptive search procedures, iterated local search, simulated annealing, tabu search, and variable neighborhood search. Applications include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the travelling salesman problem, packing and cutting, satisfiability, and general mixed integer programming.

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This book constitutes the refereed proceedings of the 13th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoBIO, EvoMUSART, and EvoApplications. The 23 revised full papers presented were carefully reviewed and selected from 50 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economic, and scientific domains. Prominent examples of metaheuristics are ant colony optimization, evolutionary algorithms, greedy randomized adaptive search procedures, iterated local search, simulated annealing, tabu search, and variable neighborhood search. Applications include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the travelling salesman problem, packing and cutting, satisfiability, and general mixed integer programming.

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This book constitutes the refereed proceedings of the 13th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoBIO, EvoMUSART, and EvoApplications. The 23 revised full papers presented were carefully reviewed and selected from 50 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economic, and scientific domains. Prominent examples of metaheuristics are ant colony optimization, evolutionary algorithms, greedy randomized adaptive search procedures, iterated local search, simulated annealing, tabu search, and variable neighborhood search. Applications include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the travelling salesman problem, packing and cutting, satisfiability, and general mixed integer programming.
Content:
Front Matter....Pages -
A Hyper-heuristic with a Round Robin Neighbourhood Selection....Pages 1-12
A Multiobjective Approach Based on the Law of Gravity and Mass Interactions for Optimizing Networks....Pages 13-24
A Multi-objective Feature Selection Approach Based on Binary PSO and Rough Set Theory....Pages 25-36
A New Crossover for Solving Constraint Satisfaction Problems....Pages 37-48
A Population-Based Strategic Oscillation Algorithm for Linear Ordering Problem with Cumulative Costs....Pages 49-60
A Study of Adaptive Perturbation Strategy for Iterated Local Search....Pages 61-72
Adaptive MOEA/D for QoS-Based Web Service Composition....Pages 73-84
An Analysis of Local Search for the Bi-objective Bidimensional Knapsack Problem....Pages 85-96
An Artificial Immune System Based Approach for Solving the Nurse Re-rostering Problem....Pages 97-108
Automatic Algorithm Selection for the Quadratic Assignment Problem Using Fitness Landscape Analysis....Pages 109-120
Balancing Bicycle Sharing Systems: A Variable Neighborhood Search Approach....Pages 121-132
Combinatorial Neighborhood Topology Particle Swarm Optimization Algorithm for the Vehicle Routing Problem....Pages 133-144
Dynamic Evolutionary Membrane Algorithm in Dynamic Environments....Pages 145-156
From Sequential to Parallel Local Search for SAT....Pages 157-168
Generalizing Hyper-heuristics via Apprenticeship Learning....Pages 169-178
High-Order Sequence Entropies for Measuring Population Diversity in the Traveling Salesman Problem....Pages 179-190
Investigating Monte-Carlo Methods on the Weak Schur Problem....Pages 191-201
Multi-objective AI Planning: Comparing Aggregation and Pareto Approaches....Pages 202-213
Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape Measures....Pages 214-225
Single Line Train Scheduling with ACO....Pages 226-237
Solving Clique Covering in Very Large Sparse Random Graphs by a Technique Based on k-Fixed Coloring Tabu Search....Pages 238-249
Solving the Virtual Network Mapping Problem with Construction Heuristics, Local Search and Variable Neighborhood Descent....Pages 250-261
The Generate-and-Solve Framework Revisited: Generating by Simulated Annealing....Pages 262-273
Back Matter....Pages -

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This book constitutes the refereed proceedings of the 13th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoBIO, EvoMUSART, and EvoApplications. The 23 revised full papers presented were carefully reviewed and selected from 50 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economic, and scientific domains. Prominent examples of metaheuristics are ant colony optimization, evolutionary algorithms, greedy randomized adaptive search procedures, iterated local search, simulated annealing, tabu search, and variable neighborhood search. Applications include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the travelling salesman problem, packing and cutting, satisfiability, and general mixed integer programming.
Content:
Front Matter....Pages -
A Hyper-heuristic with a Round Robin Neighbourhood Selection....Pages 1-12
A Multiobjective Approach Based on the Law of Gravity and Mass Interactions for Optimizing Networks....Pages 13-24
A Multi-objective Feature Selection Approach Based on Binary PSO and Rough Set Theory....Pages 25-36
A New Crossover for Solving Constraint Satisfaction Problems....Pages 37-48
A Population-Based Strategic Oscillation Algorithm for Linear Ordering Problem with Cumulative Costs....Pages 49-60
A Study of Adaptive Perturbation Strategy for Iterated Local Search....Pages 61-72
Adaptive MOEA/D for QoS-Based Web Service Composition....Pages 73-84
An Analysis of Local Search for the Bi-objective Bidimensional Knapsack Problem....Pages 85-96
An Artificial Immune System Based Approach for Solving the Nurse Re-rostering Problem....Pages 97-108
Automatic Algorithm Selection for the Quadratic Assignment Problem Using Fitness Landscape Analysis....Pages 109-120
Balancing Bicycle Sharing Systems: A Variable Neighborhood Search Approach....Pages 121-132
Combinatorial Neighborhood Topology Particle Swarm Optimization Algorithm for the Vehicle Routing Problem....Pages 133-144
Dynamic Evolutionary Membrane Algorithm in Dynamic Environments....Pages 145-156
From Sequential to Parallel Local Search for SAT....Pages 157-168
Generalizing Hyper-heuristics via Apprenticeship Learning....Pages 169-178
High-Order Sequence Entropies for Measuring Population Diversity in the Traveling Salesman Problem....Pages 179-190
Investigating Monte-Carlo Methods on the Weak Schur Problem....Pages 191-201
Multi-objective AI Planning: Comparing Aggregation and Pareto Approaches....Pages 202-213
Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape Measures....Pages 214-225
Single Line Train Scheduling with ACO....Pages 226-237
Solving Clique Covering in Very Large Sparse Random Graphs by a Technique Based on k-Fixed Coloring Tabu Search....Pages 238-249
Solving the Virtual Network Mapping Problem with Construction Heuristics, Local Search and Variable Neighborhood Descent....Pages 250-261
The Generate-and-Solve Framework Revisited: Generating by Simulated Annealing....Pages 262-273
Back Matter....Pages -
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