Metaheuristics for scheduling in industrial and manufacturing applications

This volume presents meta-heuristics approaches for scheduling problems arising in industrial and manufacturing applications. Nowadays, metaheuristics havebecome a de facto approach to tackle in practice with the complexity of scheduling problems. Early work applied evolutionary computing methods to scheduling problems. The present volume is novel in many respects. First, the proposed approaches comprise a variety of meta-heuristics (Genetic Algorithms, Memetic Algorithms, Ant Colony Optimization, Particle Swarm Optimization, Tabu Search,Scatter Search, Variable Neighborhood Search). Second, in most cases, hybridization is approached as the most effective way to achieve state-of-the art results. First book on scheduling problems in Grid, P2P and other Emergent Computational Systems INDICE: From the contents Exact, Heuristic and Meta-heuristic Algorithms for Solving Shop Scheduling Problems.- Scatter Search Algorithms for Identical Parallel Machine Scheduling Problems.- On the Effectiveness of Particle Swarm Optimization and Variable Neighborhood Descent for the Continuous Flow-Shop Scheduling Problem.- A Dynamical Ant Colony Optimization with Heuristics for Scheduling Jobs on a Single Machine with a Common Due Date.- Deterministic SearchAlgorithm for Sequencing and Scheduling.- Sequential and Parallel Variable Neighborhood Search Algorithms for Job Shop Scheduling.- Solving Scheduling Problems by Evolutionary Algorithms for Graph Coloring Problem.- Heuristics and meta-heuristics for lot sizing and scheduling in the soft drinks industry: a comparison study.- Hybrid Heuristic Approaches for Scheduling in Reconfigurable Manufacturing Systems.

• ISBN: 978-3-540-78984-0
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 345
• Fecha Publicación: 01/05/2008
• Nº Volúmenes: 1
• Idioma: Inglés