Metaheuristics for Scheduling in Industrial and Manufacturing Applications

This volume presents meta-heuristics approaches for scheduling problems arising in industrial and manufacturing applications. The present volume is the first book on scheduling problems in Grid, P2P and other Emergent Computational Systems.

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).

First book on scheduling problems in Grid, P2P and other Emergent Computational Systems Includes supplementary material: sn.pub/extras

Auteur
Dr. Ajith Abraham is Director of the Machine Intelligence Research (MIR) Labs, a global network of research laboratories with headquarters near Seattle, WA, USA. He is an author/co-author of more than 750 scientific publications. He is founding Chair of the International Conference of Computational Aspects of Social Networks (CASoN), Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing (since 2008), and a Distinguished Lecturer of the IEEE Computer Society representing Europe (since 2011).

Texte du rabat

During the past decades scheduling has been among the most studied optimization problems and it is still an active area of research! Scheduling appears in many areas of science, engineering and industry and takes different forms depending on the restrictions and optimization criteria of the operating environments.

This book deals with the application of various novel metaheuristics in scheduling. Addressing the various issues of scheduling in industrial and manufacturing applications is the novelty of this edited volume. Important features include the detailed overview of the various novel metaheuristic scheduling approaches, excellent coverage of timely, advanced scheduling topics, state-of-the-art theoretical research and application developments and chapters authored by pioneers in the field. Academics, scientists as well as engineers engaged in research, development and scheduling will find the comprehensive coverage of this book invaluable.

Contenu
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 Search Algorithm 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.- A Genetic Algorithm for Railway Scheduling Problems.- Modelling Process and Supply Chain Scheduling Using Hybrid Meta-heuristics.- Combining Simulation and Tabu Search for Oil-derivatives Pipeline Scheduling.- Particle Swarm Scheduling for Work-Flow Applications in Distributed Computing Environments.