Manufacturing systems, regardless of their size, have to work with scarce resources in dynamic environments. Managers are asked to assign production facilities over time to parallel activities respecting operational constraints and deadlines while keeping resource costs as low as possible. Thus, classic scheduling approaches are not adequate when (i) a task simultaneously requires a set of different resources and (ii) a trade-off between different objectives (like time, cost and workload balance) should be reached. In such a case, more sophisticated models and algorithms should be brought to the attention of managers and executives of manufacturing companies.

Effective Resource Management in Manufacturing Systems aims to provide robust methods for achieving effective resource allocation and to solve related problems that occur daily and often generate cost overruns, specifically focusing on problems like resource levelling, sizing of machines and production layouts, cost optimization in production planning and scheduling. This approach is based on providing quantitative methods, covering both mathematical programming and algorithms, leading to high quality solutions for the analysed problems. Details of extensive experimentation is provided for the proposed techniques to put them in a practical perspective, so that, on the one hand, the reader can reproduce them, and, on the other hand, it appears clear how they can be implemented in real scenarios.

This book will be a valuable resource for postgraduate students studying business, engineering or computer science. It will also be of interest to researchers in the fore-mentioned areas.

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 papers published in international journals. His primary research interests include: combinatorial optimization and real life scheduling and routing problems.