Advanced Models for Manufacturing Systems Management

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CRC Press, Sep 19, 1995 - Mathematics - 432 pages
This book presents the mathematical models applicable to manufacturing systems management, covering problems from production to real time control. It explores manufacturing systems from the viewpoints of both physical structure and performance measures. Two broad classes of mathematical models are covered in detail:
  • Generative models, which yield a set of decision variables optimizing a performance measure, based on mathematical optimization
  • Evaluative models, which evaluate some performance measures as a function of some predefined decision strategy. Within this class Petri Nets and Queueing Networks are discussed.
    Advanced Models for Manufacturing Systems Management describes dynamic systems modeling by state equations, a unifying framework for a wide variety of models. The text/reference stresses model building, but it examines model solving as well. Computational techniques are illustrated, such as linear programming, branch and bound methods, and dynamic programming. Particular emphasis is given to the development of heuristic methods from mathematical models.
    The book provides readers with valuable tools for management and design. The use of descriptive models within an optimization algorithm is considered. Numerous examples illustrate theoretical concepts throughout text. Appendices are given at the end of the book in order to recall fundamentals, such as linear programming and graph theory. Appendices also appear within each chapter. In this way, readers can follow the main reading path without getting involved with details; these appendices can be read at a later time. This textual structure makes this book particularly well suited for self-study. Advanced Models for Manufacturing Systems Management is beneficial reading for both students and practitioners.

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    Manufacturing systems modeling
    Optimization models and model solving
    Discretetime models
    DEDS models for scheduling problems
    Evaluative models 101
    Putting things together
    A Fundamentals of Mathematical Programming
    B Linear Programming and Network Optimization
    Enumerative and Heuristic Methods for Discrete
    Dynamic Programming
    E Stochastic modeling
    Index 300

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