Evolutionary Computation in Combinatorial Optimization: 9th European Conference, Evocop 2009, Tübingen, Germany, April 15-17, 2009, Proceedings

ISBN-13: 9783642010088 / Angielski / MiÄ™kka / 2009 / 253 str.

Carlos Cotta

Opis

Metaheuristics have been shown to be e?ective for di?cult combinatorial op- mization problems appearing in a wide variety of industrial, economic, and sci- ti?c domains. Prominent examples of metaheuristics are evolutionary algorithms, tabu search, simulated annealing, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, ant colony optimization, and estimation of distribution algorithms. Problems solved successfully include scheduling, timetabling, network design, transportation and distribution, vehicle routing, the travelling salesman problem, packing and cutting, satis?ability, and general mixed integer programming. EvoCOP began in 2001 and has been held annually since then. It is the ?rst event speci?cally dedicated to the application of evolutionary computation and related methods to combinatorial optimization problems. Originally held as a workshop, EvoCOP became a conference in 2004. The events gave researchers an excellent opportunity to present their latest research and to discuss current - velopments and applications. Following the general trend of hybrid metaheur- tics and diminishing boundaries between the di?erent classes of metaheuristics, EvoCOP has broadened its scope in recent years and invited submissions on any kind of metaheuristic for combinatorial optimization.

Spis treści

A Critical Element-Guided Perturbation Strategy for Iterated Local Search.- A Genetic Algorithm for Net Present Value Maximization for Resource Constrained Projects.- A Hybrid Algorithm for Computing Tours in a Spare Parts Warehouse.- A New Binary Description of the Blocks Relocation Problem and Benefits in a Look Ahead Heuristic.- A Plasmid Based Transgenetic Algorithm for the Biobjective Minimum Spanning Tree Problem.- A Tabu Search Algorithm with Direct Representation for Strip Packing.- An ACO Approach to Planning.- An Artificial Immune System for the Multi-Mode Resource-Constrained Project Scheduling Problem.- Beam-ACO Based on Stochastic Sampling for Makespan Optimization Concerning the TSP with Time Windows.- Binary Exponential Back Off for Tabu Tenure in Hyperheuristics.- Diversity Control and Multi-Parent Recombination for Evolutionary Graph Coloring Algorithms.- Divide-And-Evolve Facing State-of-the-Art Temporal Planners during the 6 th International Planning Competition.- Exact Solutions to the Traveling Salesperson Problem by a Population-Based Evolutionary Algorithm.- Finding Balanced Incomplete Block Designs with Metaheuristics.- Guided Ejection Search for the Job Shop Scheduling Problem.- Improving Performance in Combinatorial Optimisation Using Averaging and Clustering.- Iterated Local Search for Minimum Power Symmetric Connectivity in Wireless Networks.- Metropolis and Symmetric Functions: A Swan Song.- Robustness Analysis in Evolutionary Multi-Objective Optimization Applied to VAR Planning in Electrical Distribution Networks.- Staff Scheduling with Particle Swarm Optimisation and Evolution Strategies.- University Course Timetabling with Genetic Algorithm: A Laboratory Excercises Case Study.

Blurb

This book constitutes the refereed proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2009, held in Tübingen, Germany, in April 2009.

The 21 revised full papers presented were carefully reviewed and selected from 53 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, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms and ant colony optimization.