Effective Resource Management in Manufacturing Systems: Optimization Algorithms for Production Planning / Edition 1

Effective Resource Management in Manufacturing Systems: Optimization Algorithms for Production Planning / Edition 1

ISBN-10:
1849965420
ISBN-13:
9781849965422
Pub. Date:
12/08/2010
Publisher:
Springer London
ISBN-10:
1849965420
ISBN-13:
9781849965422
Pub. Date:
12/08/2010
Publisher:
Springer London
Effective Resource Management in Manufacturing Systems: Optimization Algorithms for Production Planning / Edition 1

Effective Resource Management in Manufacturing Systems: Optimization Algorithms for Production Planning / Edition 1

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Overview

Manufacturing systems work with scarce resources in dynamic environments. Managers need to assign production facilities to parallel activities, respecting operational constraints and deadlines while keeping costs low. Old scheduling approaches are inadequate when a task both requires a set of different resources and a trade-off between objectives. More sophisticated models and algorithms are needed by these managers.

This book provides robust methods for achieving effective resource allocation. It also solves problems such as resource levelling, sizing of machines and production layouts, cost optimization in production planning and scheduling that occur daily and often generate cost overruns. The quantitative methods used cover both mathematical programming and algorithms, leading to high quality solutions. Details of experimentation put these techniques in a practical perspective.

This book is a valuable resource for postgraduate students and researchers in business, engineering or computer science.


Product Details

ISBN-13: 9781849965422
Publisher: Springer London
Publication date: 12/08/2010
Series: Springer Series in Advanced Manufacturing
Edition description: Softcover reprint of hardcover 1st ed. 2006
Pages: 216
Product dimensions: 6.10(w) x 9.25(h) x 0.36(d)

About the Author

Massimiliano Caramia received his Laurea Degree in Management Engineering at the University of Rome "Tor Vergata", Italy in 1996, and his Ph.D. in Operations Research at the University of Rome "La Sapienza" in 2000. From 2000 to 2001 he was a research associate at the University of Rome "Tor Vergata", since then he has been a researcher at the Istituto per le Applicazioni del Calcolo "M. Picone" of the Italian National Research Council. His primary research interests include: combinatorial optimization, manufacturing, real life scheduling problems and logistics. He has published many papers in international journals such as Discrete Mathematics and SIAM Journal on Optimization, Networks, and has acted as a referee for many international journals, including: Journal of Discrete Algorithms, Transportation Science and International Transactions in Operational Research. His teaching subjects are Operations Research, Models and Analysis of Manufacturing Systems, Mathematical Methods for Management, Decision Support Systems, Quality and Performance Management, Project Management.

Paolo Dell’Olmo received his Laurea Degree in Electronic Engineering at the University of Rome "La Sapienza", Italy. He became a full professor in Operations Research in 2000. He has been a visiting scholar at the Department of Systems and Industrial Engineering of University of Arizona (1992-93), a visiting professor at the Operation Research Center of MIT (1998). Currently, he is: Head of the Department of Statistics, Probability and Applied Statistics at the University of Rome "La Sapienza", he is also a Director of the Masters degree in Data Intelligence and Strategic Decisions and coordinator of the PhD program in Operations Research of the University of Rome as well as a research fellow of the Istituto di Analisi dei Sistemi e Informatica. He has been responsible for several national and international research projects and author of more than 60 scientific paperspublished in international journals. His primary research interests include: combinatorial optimization and real life scheduling and routing problems.

Table of Contents

Manufacturing Systems: Trends, Classification, and Behavior Patterns.- On-Line Load Balancing.- Resource Levelling.- Scheduling Jobs in Robotized Cells with Multiple Shared Resources.- Tool Management on Flexible Machines.
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