Evolutionary Computation in Combinatorial Optimization

Description

Evolutionary Computation in Combinatorial Optimization: 4th European Conference, EvoCOP 2004, Coimbra, Portugal, April 5-7, 2004. Proceedings<br />Author: Jens Gottlieb, Günther R. Raidl<br /> Published by Springer Berlin Heidelberg<br /> ISBN: 978-3-540-21367-3<br /> DOI: 10.1007/b96499<br /><br />Table of Contents:<p></p><ul><li>Mutation Multiplicity in a Panmictic Two-Strategy Genetic Algorithm </li><li>Solving the Vehicle Routing Problem by Using Cellular Genetic Algorithms </li><li>Landscape Regularity and Random Walks for the Job-Shop Scheduling Problem </li><li>A Comparison of Adaptive Operator Scheduling Methods on the Traveling Salesman Problem </li><li>AntPacking – An Ant Colony Optimization Approach for the One-Dimensional Bin Packing Problem </li><li>Scatter Search and Memetic Approaches to the Error Correcting Code Problem </li><li>A Hybrid Evolutionary Algorithm for Solving the Register Allocation Problem </li><li>Parallel Ant Systems for the Capacitated Vehicle Routing Problem </li><li>A Hierarchical Social Metaheuristic for the Max-Cut Problem </li><li>On the Structure of Sequential Search: Beyond “No Free Lunch” </li><li>Dealing with Solution Diversity in an EA for Multiple Objective Decision Support – A Case Study </li><li>A Study into Ant Colony Optimisation, Evolutionary Computation and Constraint Programming on Binary Constraint Satisfaction Problems </li><li>Binary Merge Model Representation of the Graph Colouring Problem </li><li>Hardness Prediction for the University Course Timetabling Problem </li><li>Hybrid Estimation of Distribution Algorithm for Multiobjective Knapsack Problem </li><li>On the Use of Path Relinking for the ρ – Hub Median Problem </li><li>Solving a Real-World Glass Cutting Problem </li><li>Designing Reliable Communication Networks with a Genetic Algorithm Using a Repair Heuristic </li><li>Improving Vehicle Routing Using a Customer Waiting Time Colony </li><li>New Benchmark Instances for the QAP and the Experimental Analysis of Algorithms</li></ul>

First Sentence

Genetic algorithms (GA s) are biologically inspired search procedures that have been used successfully for the solution of hard numerical and combinatorial optimization problems.

Subjects

Other Editions

• Evolutionary Computation in Combinatorial Optimization: 4th European Conference, EvoCOP 2004, Coimbra, Portugal, April 5-7, 2004, Proceedings (Lecture Notes in Computer Science)PaperbackSpringer2004-05-14
• Evolutionary Computation in Combinatorial OptimizationSpringer London, Limited2004-01-01
• Evolutionary Computation in Combinatorial OptimizationSpringer London, Limited2005-01-01