This book introduces a novel approach to discrete optimization, providing both theoretical insights and algorithmic developments that lead to improvements over state-of-the-art technology. The authors present chapters on the use of decision diagrams for combinatorial optimization and constraint programming, with attention to general-purpose solution methods as well as problem-specific techniques. The book will be useful for researchers and practitioners in discrete optimization and constraint programming. Decision Diagrams for Optimization is one of the most exciting developments emerging from constraint programming in recent years. This book is a compelling summary of existing results in this space and a must-read for optimizers around the world. [Pascal Van Hentenryck]
This book presents for the first time a methodology that combines the power of a modelling formalism such as colored petri nets with the flexibility of a discrete event program such as SIMIO. Industrial practitioners have seen the growth of simulation as a methodology for tacking problems in which variability is the common denominator. Practically all industrial systems, from manufacturing to aviation are considered stochastic systems. Different modelling techniques have been developed as well as mathematical techniques for formalizing the cause-effect relationships in industrial and complex systems. The methodology in this book illustrates how complexity in modelling can be tackled by the use of coloured petri nets, while at the same time the variability present in systems is integrated in a robust fashion. The book can be used as a concise guide for developing robust models, which are able to efficiently simulate the cause-effect relationships present in complex industrial systems without losing the simulation power of discrete-event simulation. In addition SIMIOs capabilities allows integration of features that are becoming more and more important for the success of projects such as animation, virtual reality, and geographical information systems (GIS). Dr Miguel Mujica Mota is a researcher and lecturer at the Aviation Academy of the Amsterdam University of Applied Sciences in the Netherlands. He was previously the sub director of the aviation studies at the Autonomous University of Barcelona. He holds a PhD and a MSc. in industrial informatics from the Autonomous University of Barcelona and a PhD and MSc. in operations research from the National University of Mexico, all obtained with the highest honors. Dr. Mujica Mota has given several courses in modelling, simulation methodologies and optimization in different countries for industrial and academic audiences. He has participated in several international projects in which simulation and optimization were the key factors for the success of them. Dr. Mujica has been awarded with the Level C of the Mexican Council of Science and Technology where he also participates as a scientific evaluator for Latin America. He is the co-author of two books and numerous papers on simulation, operations research, aviation, manufacturing and logistics. His research interests lie in the use of simulation, modelling formalisms and heuristics for the optimization and performance analysis of aeronautical operations, manufacture and logistics. Miquel Àngel Piera received his MSc (Control Engineering) from the University of Manchester Institute of Technology in 1990 and his PhD degree from the Autonomous University of Barcelona (Spain) in 1994. He participates in industrial research projects in the logistics and manufacturing field and at present he is Co-director of LogiSim, a Modelling and Simulation Institution sponsored and founded by the local government of Catalonia. Recently, he has published a modelling and simulation book that is being used for teaching in many Spanish universities. Dr. Antoni Guasch is a research engineer focusing on modelling, simulation and optimization of dynamic systems, especially continuous and discrete-event simulation of industrial processes. He received his Ph.D. from the UPC in 1987. After a postdoctoral period at the State University of California (USA), he becomes a Professor of the UPC (www.upc.edu ). He is now Professor in the department of Ingeniería de Sistemas, Automática e Informática Industrial in the UPC and head of Simulation and Industrial Optimization at inLab FIB (http://inlab.fib.upc.edu/). Since 1990, Prof Guasch has lead more than 40 industrial projects related with modelling, simulation and optimization of nuclear, textile, transportation, car manufacturing, water, steel, pharmaceutical and banking processes. Dr. Guasch has also been the Scientific Co-ordinator and researcher in 7 scientific projects He has participated in 4 EU projects, with the role of partner leader in two of them. Dr. Guasch currently research projected is related to the development of algorithms for the optimal management of air resources for forest fire containmentDr. Idalia Flores de la Mota received a Master with honors, being awarded the Gabino Barreda Medal for the best average of her generation, in the Faculty of Engineering of the UNAM, where she also obtained her Ph.D. in Operations Research. Dr. Flores is a referee and a member of various Academic
Bachelorarbeit aus dem Jahr 2014 im Fachbereich Informatik - Wirtschaftsinformatik, Note: 1,3, Hochschule Deggendorf, Sprache: Deutsch, Abstract: Diese Arbeit behandelt das Thema Software Asset Management (SAM). Man kann SAM als Geschäftspraxis bezeichnen, die sich um die Einkaufsoptimierung und Verwaltung, sowie die Bereitstellung, Wartung, Nutzung und der Entsorgung von Software-Anwendungen innerhalb eines Unternehmens kümmert. In dieser Arbeit wird gezeigt, warum der Einsatz von SAM sinnvoll ist und wie Prozesse bei der Einführung von SAM optimiert werden können. Nach einer theoretischen Auseinandersetzung mit dem Thema, wird die Theorie anhand der Microsoft SAM Lösung aufgezeigt. Microsoft unterteilt hierbei ihre SAM Lösung in drei Bereiche: ? Sam Baseline ? SAM Assessment ? SAM Deployment Planning Im SAM Assessment werden die Prozesse aufgezeigt, die in einem Unternehmen implementiert werden sollten, um SAM dauerhaft zu leben. Durch ein SAM-Projekt wird Schritt für Schritt auf die Verbesserung der Prozesse hingearbeitet, da Probleme und Fehlverhalten aufgedeckt werden können. Im SAM - Deployment Planning gilt es dann, die entdeckten Probleme zu besprechen und Lösungen dafür zu finden. Die grundlegendsten Prozesse werden in der Arbeit grafisch dargestellt und analysiert.
Akademische Arbeit aus dem Jahr 2012 im Fachbereich Informatik - Wirtschaftsinformatik, Note: 1,3, FernUniversität Hagen, Sprache: Deutsch, Abstract: Viele Unternehmen stehen in der Phase des Strategischen Prozessmanagements und damit kurz vor dem nächsten Schritt: der Modellierung von Prozessen. Dabei stellt sich die Frage, mit welcher Modellierungsmethode Prozessmanagement erfolgreich durchgeführt werden kann und wie auf lange Sicht durch Prozessautomatisierung erhöhte Effektivität und Effizienz erlangt werden kann. Dazu wird in Kapitel 1.1 ein Kriterienkatalog aufgestellt, welcher einen Vergleich der Methoden ermöglichen soll. Dann werden im nächsten Kapitel vier Methoden aus der Vielzahl der derzeit am Markt bestehenden Standards ausgewählt. Diese werden anschließend in Kapitel 1.3 beschrieben und durch ein Beispiel visualisiert. Ziel ist, am Ende des Vergleichs in Kapitel 1.4 eine Methode auszuwählen, die Unternehmen innerhalb des Geschäftsprozessmanagements am besten unterstützt.
This proceedings book presents selected contributions from the XVIII Congress of APDIO (the Portuguese Association of Operational Research) held in Valença on June 28-30, 2017. Prepared by leading Portuguese and international researchers in the field of operations research, it covers a wide range of complex real-world applications of operations research methods using recent theoretical techniques, in order to narrow the gap between academic research and practical applications. Of particular interest are the applications of, nonlinear and mixed-integer programming, data envelopment analysis, clustering techniques, hybrid heuristics, supply chain management, and lot sizing and job scheduling problems. In most chapters, the problems, methods and methodologies described are complemented by supporting figures, tables and algorithms. The XVIII Congress of APDIO marked the 18th installment of the regular biannual meetings of APDIO - the Portuguese Association of Operational Research. The meetings bring together researchers, scholars and practitioners, as well as MSc and PhD students, working in the field of operations research to present and discuss their latest works. The main theme of the latest meeting was Operational Research Pro Bono. Given the breadth of topics covered, the book offers a valuable resource for all researchers, students and practitioners interested in the latest trends in this field.
This book presents methods for full-wave computer simulation that can be used in various applications and contexts, e.g. seismic prospecting, earthquake stability, global seismic patterns on Earth and Mars, medicine, traumatology, ultrasound investigation of the human body, ultrasound and laser operations, ultrasonic non-destructive railway testing, modelling aircraft composites, modelling composite material delamination, etc. The key innovation of this approach is the ability to study spatial dynamical wave processes, which is made possible by cutting-edge numerical finite-difference grid-characteristic methods. The book will benefit all students, researchers, practitioners and professors interested in numerical mathematics, computer science, computer simulation, high-performance computer systems, unstructured meshes, interpolation, seismic prospecting, geophysics, medicine, non-destructive testing and composite materials.
This volume provides a unique collection of mathematical tools and industrial case studies in digital manufacturing. It addresses various topics, ranging from models of single production technologies, production lines, logistics and workflows to models and optimization strategies for energy consumption in production. The digital factory represents a network of digital models and simulation and 3D visualization methods for the holistic planning, realization, control and ongoing improvement of all factory processes related to a specific product. In the past ten years, all industrialized countries have launched initiatives to realize this vision, sometimes also referred to as Industry 4.0 (in Europe) or Smart Manufacturing (in the United States). Its main goals are • reconfigurable, adaptive and evolving factories capable of small-scale production • high-performance production, combining flexibility, productivity, precision and zero defects • energy and resource efficiency in manufacturing None of these goals can be achieved without a thorough modeling of all aspects of manufacturing together with a multi-scale simulation and optimization of process chains; in other words, without mathematics. To foster collaboration between mathematics and industry in this area the European Consortium for Mathematics in Industry (ECMI) founded a special interest group on Math for the Digital Factory (M4DiFa). This book compiles a selection of review papers from the M4DiFa kick-off meeting held at the Weierstrass Institute for Applied Analysis and Stochastics in Berlin, Germany, in May 2014. The workshop aimed at bringing together mathematicians working on modeling, simulation and optimization with researchers and practitioners from the manufacturing industry to develop a holistic mathematical view on digital manufacturing. This book is of interest to practitioners from industry who want to learn about important mathematical concepts, as well as to scientists who want to find out about an exciting new area of application that is of vital importance for todays highly industrialized and high-wage countries.
This book presents state-of-the-art results and methodologies in modern global optimization, and has been a staple reference for researchers, engineers, advanced students (also in applied mathematics), and practitioners in various fields of engineering. The second edition has been brought up to date and continues to develop a coherent and rigorous theory of deterministic global optimization, highlighting the essential role of convex analysis. The text has been revised and expanded to meet the needs of research, education, and applications for many years to come. Updates for this new edition include : · Discussion of modern approaches to minimax, fixed point, and equilibrium theorems, and to nonconvex optimization; · Increased focus on dealing more efficiently with ill-posed problems of global optimization, particularly those with hard constraints; · Important discussions of decomposition methods for specially structured problems; · A complete revision of the chapter on nonconvex quadratic programming, in order to encompass the advances made in quadratic optimization since publication of the first edition. · Additionally, this new edition contains entirely new chapters devoted to monotonic optimization, polynomial optimization and optimization under equilibrium constraints, including bilevel programming, multiobjective programming, and optimization with variational inequality constraint. From the reviews of the first edition : The book gives a good review of the topic. ... The text is carefully constructed and well written, the exposition is clear. It leaves a remarkable impression of the concepts, tools and techniques in global optimization. It might also be used as a basis and guideline for lectures on this subject. Students as well as professionals will profitably read and use it. - Mathematical Methods of Operations Research, 49:3 (1999)
Über diese Methodensammlung Dieses Buch, enthält eine Sammlung von wichtigen Methoden und Techniken in kompakter und gekürzter Form. Diese Sammlung hat nicht den Anspruch, Methoden und Techniken vorzustellen und zu erklären. Sie dient als Nachschlagewerk, welche erlaubt, einmal erlernte Methoden und Techniken auf einen Blick wieder in Erinnerung zu rufen und deren Details, wie z.B. Notationen, nachzuschlagen. Durch viele Abbildungen und Beispiele wird dieser Effekt noch verstärkt. Die Suche nach Methoden und Techniken erfolgt über den Index. Dabei wurde darauf geachtet, dass die einzelnen Methoden und Techniken zusätzlich mit deren Abkürzungen und Alternativbegriffen gefunden werden können.
This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives. The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.