This textbook offers a comprehensive, up-to-date introduction to the Optimization Programming Language (OPL). Embedded in the IBM ILOG CPLEX Optimization Studio with its solver engine CPLEX, OPL has been popular for years not only for academic and scientific purposes, but also among practitioners who need to model and solve large-scale real-world business optimization problems. The book covers the recent features of the software and includes ten consecutive tutorials, each with additional exercises, as well as several comprehensive application studies. The book is specifically designed for advanced undergraduate and graduate courses in e.g. management science, operations research, computer science, mathematics, mathematical economics, and industrial engineering. It can also serve as self-study material for practitioners whose work involves the modeling and optimization of planning and decision problems and who need a sound introduction to the software. Solutions to the exercises as well as the source codes from the textbook are available for download (weblink included).

Today many organizations face challenges when developing a realistic plan or schedule that provides the best possible balance between customer service and revenue goals. Optimization technology has long been used to find the best solutions to complex planning and scheduling problems. A decision-support environment that enables the flexible exploration of all the trade-offs and sensitivities needs to provide the following capabilities: Flexibility to develop and compare realistic planning and scheduling scenarios Quality sensitivity analysis and explanations Collaborative planning and scenario sharing Decision recommendations This IBM® Redbooks® publication introduces you to the IBM ILOG® Optimization Decision Manager (ODM) Enterprise. This decision-support application provides the capabilities you need to take full advantage of optimization technology. Applications built with IBM ILOG ODM Enterprise can help users create, compare, and understand planning or scheduling scenarios. They can also adjust any of the model inputs or goals, and fully understanding the binding constraints, trade-offs, sensitivities, and business options. This book enables business analysts, architects, and administrators to design and use their own operational decision management solution.

This contributed volume presents a collection of materials on supply chain management including industry-based case studies addressing petrochemical, pharmaceutical, manufacturing and reverse logistics topics. Moreover, the book covers sustainability issues, as well as optimization approaches. The target audience comprises academics, industry managers, and practitioners in the field of supply chain management, being the book also beneficial for graduate students

This book constitutes the refereed proceedings of the 21st International Conference on Software Engineering and Formal Methods, SEFM 2023, held in Eindhoven, The Netherlands, during November 6-10, 2023. The 18 regular papers presented in this book, together with 1 invited paper and 1 tool paper, were carefully reviewed and selected from 41 submissions. The SEFM conference series aims to bring together researchers and practitioners from academia, industry and government, to advance the state of the art in formal methods, to facilitate their uptake in the software industry, and to encourage their integration within practical software engineering methods and tools.

This book presents the proceedings of the 3rd Conference on Computer Science, Electronics, and Industrial Engineering (CSEI 2021), held in Ambato in October 2021, with participants from 10 countries and guest speakers from Chile, Colombia, Brasil, Spain, Portugal, and United States. Featuring 20 peer-reviewed papers, it discusses topics such as the use of metaheuristics for non-deterministic problem solutions, software architectures for supporting e-government initiatives, and the use of electronics in e-learning and industrial environments. It also includes contributions illustrating how new approaches to these converging research areas are impacting the development of human societies around the world. As such, it is a valuable resource for scholars and practitioners alike.

Business Analytics for Decision Making, the first complete text suitable for use in introductory Business Analytics courses, establishes a national syllabus for an emerging first course at an MBA or upper undergraduate level. This timely text is mainly about model analytics, particularly analytics for constrained optimization. It uses implementations that allow students to explore models and data for the sake of discovery, understanding, and decision making. Business analytics is about using data and models to solve various kinds of decision problems. There are three aspects for those who want to make the most of their analytics: encoding, solution design, and post-solution analysis. This textbook addresses all three. Emphasizing the use of constrained optimization models for decision making, the book concentrates on post-solution analysis of models. The text focuses on computationally challenging problems that commonly arise in business environments. Unique among business analytics texts, it emphasizes using heuristics for solving difficult optimization problems important in business practice by making best use of methods from Computer Science and Operations Research. Furthermore, case studies and examples illustrate the real-world applications of these methods. The authors supply examples in Excel®, GAMS, MATLAB®, and OPL. The metaheuristics code is also made available at the book's website in a documented library of Python modules, along with data and material for homework exercises. From the beginning, the authors emphasize analytics and de-emphasize representation and encoding so students will have plenty to sink their teeth into regardless of their computer programming experience.

As populations have continued to grow and expand, many people have made their homes in cities around the globe. With this increase in city living, it is becoming vital to create intelligent urban environments that efficiently support this growth and simultaneously provide friendly and progressive environments to both businesses and citizens alike. Smart Cities and Smart Spaces: Concepts, Methodologies, Tools, and Applications is an innovative reference source that discusses social, economic, and environmental issues surrounding the evolution of smart cities. Highlighting a range of topics such as smart destinations, urban planning, and intelligent communities, this multi-volume book is designed for engineers, architects, facility managers, policymakers, academicians, and researchers interested in expanding their knowledge on the emerging trends and topics involving smart cities.

IBM® defines a smarter city as one that makes optimal use of all available information to better understand and control its operations and optimize the use of resources. There is much information available from different sources. However, city officials often lack the holistic view of the city's operations that is required to respond to the citizens' needs in a timely manner and use the city resources wisely. IBM Intelligent Operations Center delivers a unified view of city agencies, providing three primary elements for successful management of cities: use information, anticipate problems, and coordinate actions and resources. Chapter 1 of this IBM Redbooks® publication introduces the IBM Intelligent Operations Center solution. The chapter provides a high-level overview of its features, benefits, and architecture. This information is intended for city officials and IT architects that must understand the business value of IBM Intelligent Operations Center and its architecture. The remaining chapters of this book focus on information that help IBM Intelligent Operations Center administrators perform daily administration tasks. This book describes commands and tools that IBM Intelligent Operations Center administrators must use to keep the solution running, troubleshoot and diagnose problems, and perform preventive maintenance. This book includes preferred practices, tips and techniques, and general suggestions for administrators of IBM Intelligent Operations Center on-premises deployments. For related information about this topic, refer to the following IBM Redbooks publications: IBM Intelligent Operations Center for Smarter Cities Redpaper, REDP-4939 IBM Intelligent Operations Center for Smarter Cities Solution Guide

The field of Chemical Engineering and its link to computer science is in constant evolution and new engineers have a variety of tools at their disposal to tackle their everyday problems. Introduction to Software for Chemical Engineers, Second Edition provides a quick guide to the use of various computer packages for chemical engineering applications. It covers a range of software applications from Excel and general mathematical packages such as MATLAB and MathCAD to process simulators, CHEMCAD and ASPEN, equation-based modeling languages, gProms, optimization software such as GAMS and AIMS, and specialized software like CFD or DEM codes. The different packages are introduced and applied to solve typical problems in fluid mechanics, heat and mass transfer, mass and energy balances, unit operations, reactor engineering, process and equipment design and control. This new edition offers a wider view of packages including open source software such as R, Python and Julia. It also includes complete examples in ASPEN Plus, adds ANSYS Fluent to CFD codes, Lingo to the optimization packages, and discusses Engineering Equation Solver. It offers a global idea of the capabilities of the software used in the chemical engineering field and provides examples for solving real-world problems. Written by leading experts, this book is a must-have reference for chemical engineers looking to grow in their careers through the use of new and improving computer software. Its user-friendly approach to simulation and optimization as well as its example-based presentation of the software, makes it a perfect teaching tool for both undergraduate and master levels.

This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016. The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions. These proceedings contain papers in the fields of Machine Learning, Computational Optimization and DataScience presenting a substantial array of ideas, technologies, algorithms, methods and applications.