Introduction To Cutting And Packing Optimization
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Introduction to Cutting and Packing Optimization
This book provides a comprehensive overview of the most important and frequently considered optimization problems concerning cutting and packing. Based on appropriate modeling approaches for the problems considered, it offers an introduction to the related solution methods. It also addresses aspects like performance results for heuristic algorithms and bounds of the optimal value, as well as the packability of a given set of objects within a predefined container. The problems discussed arise in a wide variety of different fields of application and research, and as such, the fundamental knowledge presented in this book make it a valuable resource for students, practitioners, and researchers who are interested in dealing with such tasks.
Intelligent Algorithms for Packing and Cutting Problem
This book investigates in detail the two-dimensional packing and cutting problems in the field of operations research and management science. It introduces the mathematical models and intelligent solving algorithms for these problems, as well as their engineering applications. Most intelligent methods reported in this book have already been applied in reality, which can provide reference for the engineers. The presented novel methods for the two-dimensional packing problem provide a new way to solve the problem for researchers interested in operations research or computer science. This book also introduces three new variants of packing problems and their solving methods, which offer a different research direction. The book is intended for undergraduate and graduate students who are interested in the solving methods for packing and cutting problems, researchers investigating the application of intelligent algorithms, scientists studying the theory of the operations research and CAM software developers working on integration of packing and cutting problem.
Optimization Essentials
This book explores recent developments and exciting challenges in operations research and mathematical optimization. It provides the following in a unified and carefully developed presentation: (a) novel problems that have arisen in the real-life optimization domain, highlighting the challenges in each problem; (b) significant methodological advances for solving existing optimization problems, with a special emphasis on large scale problems. The book assumes a decent understanding of matrix algebra, linear and integer programming, non-linear programming, computational complexity, and graph theory. Each chapter in this book starts with an introduction to the underlying optimization technique. It then explores a real-life case study to which the technique will be applied. The objective is to demonstrate how the underlying technique can be utilized to solve a challenging problem. The chapters offer details on how to formulate a research problem into a formal optimization model, reformulate or transform it (if required) to improve computational tractability, and apply necessary customizations to the optimization technique specific to the underlying problem to derive an optimal or near-optimal solution. The book covers various state-of-the-art methods (both exact and heuristics) and modelling approaches in sync with the current research trends, which are still not discussed in typical graduate-level textbooks. Applications covered in the book span the realms of resource planning, telecommunications, scheduling, logistics, education, environmental conservation, and many others. It is thus a valuable resource for post-graduate students of operations research and mathematical optimization. It also serves as a valuable reference for researchers who wish to explore various optimization techniques as part of their research methodologies. The learning from the book should enable the professionals to apply optimization theory and algorithms to their particular field of interest.