Metaheuristics for Scheduling in Industrial and Manufacturing Applications

Ajith Abraham

ISBN 10: 3642097782 / ISBN 13: 9783642097782

Edité par Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2010, 2010

A propos de cet article

This item is printed on demand - Print on Demand Titel. Neuware -During the past decades scheduling has been among the most studied op- mization problemsanditisstillanactiveareaofresearch!Schedulingappears in many areas of science, engineering and industry and takes di erent forms depending on the restrictions and optimization criteria of the operating en- ronments [8]. For instance, in optimization and computer science, scheduling has been de ned as ¿the allocation of tasks to resources over time in order to achieve optimality in one or more objective criteria in an e cient way¿ and in production as ¿production schedule, i. e. , the planning of the production or the sequence of operations according to which jobs pass through machines and is optimal with respect to certain optimization criteria. ¿ Although there is a standardized form of stating any scheduling problem, namely ¿e cient allocation ofn jobs onm machines ¿which can process no more than one activity at a time¿ with the objective to optimize some - jective function of the job completion times¿, scheduling is in fact a family of problems. Indeed, several parameters intervene in the problem de nition: (a) job characteristics (preemptive or not, precedence constraints, release dates, etc. ); (b) resource environment (single vs. parallel machines, un- lated machines, identical or uniform machines, etc. ); (c) optimization criteria (minimize total tardiness, the number of late jobs, makespan, owtime, etc. ; maximize resource utilization, etc. ); and, (d) scheduling environment (static vs. dynamic,intheformerthenumberofjobstobeconsideredandtheirready times are available while in the later the number of jobs and their charact- istics change over time).Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 372 pp. Englisch.

N° de réf. du vendeur 9783642097782

Détails bibliographiques

• Titre: Metaheuristics for Scheduling in Industrial and Manufacturing Applications
• Éditeur: Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2010
• Date de parution: 2010
• Langue: anglais
• ISBN à 10 chiffres: 3642097782
• ISBN à 13 chiffres: 9783642097782
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 235 L x 155 H x 21 P (en millimètres) 235 millimètres de largeur par 155 millimètres de hauteur par 21 millimètres de profondeur
• Poids: 563 grammes

A propos de ce titre

Synopsis

During the past decades scheduling has been among the most studied op- mization problemsanditisstillanactiveareaofresearch!Schedulingappears in many areas of science, engineering and industry and takes di?erent forms depending on the restrictions and optimization criteria of the operating en- ronments [8]. For instance, in optimization and computer science, scheduling has been de?ned as “the allocation of tasks to resources over time in order to achieve optimality in one or more objective criteria in an e?cient way” and in production as “production schedule, i. e. , the planning of the production or the sequence of operations according to which jobs pass through machines and is optimal with respect to certain optimization criteria. ” Although there is a standardized form of stating any scheduling problem, namely “e?cient allocation ofn jobs onm machines –which can process no more than one activity at a time– with the objective to optimize some - jective function of the job completion times”, scheduling is in fact a family of problems. Indeed, several parameters intervene in the problem de?nition: (a) job characteristics (preemptive or not, precedence constraints, release dates, etc. ); (b) resource environment (single vs. parallel machines, un- lated machines, identical or uniform machines, etc. ); (c) optimization criteria (minimize total tardiness, the number of late jobs, makespan, ?owtime, etc. ; maximize resource utilization, etc. ); and, (d) scheduling environment (static vs. dynamic,intheformerthenumberofjobstobeconsideredandtheirready times are available while in the later the number of jobs and their charact- istics change over time).

Présentation de l'éditeur

This volume presents meta-heuristics approaches for scheduling problems arising in industrial and manufacturing applications. Nowadays, metaheuristics have become 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. Third, and most importantly, the scheduling problems arising in real life applications and real world data instances are solved using these meta-heuristics; these applications comprise reconfigurable manufacturing systems, lot sizing and scheduling in industry, railway scheduling and process, supply chain scheduling and scheduling problem arising in a real-world multi-commodity Oil-derivatives Pipeline. Finally, scheduling problems and meta-heuristics are presented in a comprehensive way making this volume and interesting contribution to the research on scheduling in industrial and manufacturing applications.