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Besides scheduling problems for single and parallel machines and shop scheduling problems the book covers advanced models involving due-dates, sequence dependent changeover times and batching. Also multiprocessor task scheduling and problems with multi-purpose machines are discussed. The methods used to solve these problems are linear programming, dynamic programming, branch-and-bound algorithms, and local search heuristics. Complexity results for different classes of deterministic scheduling problems are summerized.

Computer capacity --- Production scheduling. --- Computer algorithms. --- Capacité de traitement --- Ordonnancement (Gestion) --- Algorithmes --- Planning. --- Planification --- Computer capacity. --- Engineering & Applied Sciences --- Computer Science --- Production scheduling --- Computer algorithms --- Management Theory --- Management --- Business & Economics --- Planning --- Capacité de traitement --- EPUB-LIV-FT LIVECONO LIVGESTI SPRINGER-B --- Job scheduling (Production control) --- Job-shop scheduling --- Project scheduling (Production control) --- Scheduling (Management) --- Business. --- Production management. --- Operations research. --- Decision making. --- Management science. --- Business and Management. --- Operation Research/Decision Theory. --- Operations Research, Management Science. --- Operations Management. --- Production control --- Scheduling --- Algorithms --- Operations Research/Decision Theory. --- Manufacturing management --- Industrial management --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Quantitative business analysis --- Problem solving --- Operations research --- Statistical decision --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management decisions --- Choice (Psychology) --- Decision making

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Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computational techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, are derived from biologically inspired concepts and are well-suited to solve scheduling problems since they are highly scalable and flexible in terms of handling constraints and multiple objectives. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling, and demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems. The intended readers of this book are engineers, researchers, practitioners, senior undergraduates, and graduate students who are interested in the field of evolutionary scheduling.

Evolutionary computation. --- Computer scheduling. --- Computational intelligence. --- Réseaux neuronaux à structure évolutive --- Ordonnancement (Informatique) --- Intelligence informatique --- Evolutionary computation --- Computer scheduling --- Computational intelligence --- Applied Mathematics --- Civil Engineering --- Computer Science --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Intelligence, Computational --- Electronic data processing --- Processor scheduling (Electronic data processing) --- Scheduling of electronic data processing --- Computation, Evolutionary --- Scheduling --- Computer science. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Appl.Mathematics/Computational Methods of Engineering. --- Production scheduling --- Time-sharing computer systems --- Neural networks (Computer science) --- Artificial intelligence --- Soft computing --- Artificial Intelligence. --- Mathematical and Computational Engineering. --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Mathematics