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​This book presents practical algorithms for solving a wide variety of cutting and packing problems from the perspective of combinatorial optimization. Problems of cutting and packing objects in one-, two-, or three-dimensional space have been extensively studied for many years because of numerous real applications—for instance, in the clothing, logistics, manufacturing, and material industries. Cutting and packing problems can be classified in three ways according to their dimensions: The one-dimensional problem is the most basic category of problems including knapsack problems, bin packing problems, and cutting stock problems, among others. The two-dimensional problem is a category of geometric problems including rectangle packing problems, circle packing problems, and polygon packing problems, among others. The three-dimensional problem is the most difficult category of problems and has applications in container loading, cargo and warehouse management and so forth. Most of these variants are NP-hard, since they contain as a special case the knapsack problem or the bin packing problem, which are already known to be NP-hard. Therefore, heuristics and metaheuristics are very important to design practical algorithms for these problems. We survey practical algorithms for solving a wide variety of cutting and packing problems in this book. Another feature of cutting and packing problems is the requirement to develop powerful geometric tools to handle the wide variety and complexity of shapes that need to be packed. We also survey geometric properties and tools for cutting and packing problems in the book.
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.
1 Introduction.- 1.1. Purpose of the Investigation.- 1.2. Methodology Used.- 1.3. Structure of the Book.- 2 Cutting and Packing Problems as Geometric-Combinatoric Problems.- 2.1. Basic Logical Structure.- 2.2. Phenomena of Cutting and Packing.- 2.2.1. Cutting and Packing in Spatial Dimensions.- 2.2.2. Cutting and Packing in Abstract Dimensions.- 2.2.3. Related Problems.- 2.3. Delimitation in Investigation.- 3 The Treatment of Cutting and Packing Problems in the Literature.- 3.1. Models as Idealized Images of Actual Phenomena.- 3.2. Sources on Cutting and Packing Problems.- 3.2.1. Differentiation According to Thematic Criteria.- 3.2.2. Differentiation According to Bibliographical Criteria.- 3.3. Delimitation of Investigated Literature.- 4 Systematic Catalogue of Properties for the Characterization of Cutting and Packing Problems.- 4.1. Basis for Characteristic Properties.- 4.2. Design of the Catalogue.- 4.3. Characteristics Based on the Logical Structure.- 4.3.1. Dimensionality.- 4.3.2. Type of Assignment.- 4.3.3. Characteristics of Large Objects and Small Items.- 4.3.4. Pattern Restrictions.- 4.3.5. Objectives.- 4.3.6. Status of Information and Variability of Data.- 4.3.7. Solution Methods.- 4.4. Reality-Based Characteristics.- 4.4.1. Kind of Objects and Items, and Branch of Industry.- 4.4.2. Planning Context.- 4.4.3. Software.- 4.5. Overview.- 5 Types of Cutting and Packing Problems in the Literature.- 5.1. Principles of Type Definition.- 5.2. Hierarchical Catalogue of Types.- 5.2.1. General Types.- 5.2.2. Special Types.- 5.2.3. Summarized Description of the Hierarchy of Types.- 5.3. Properties of the Derived Problem Types.- 6 Bin Packing Types (BP).- 6.1. One-dimensional Bin Packing Type (BP1).- 6.2. Two-dimensional Bin Packing Types (BP2).- 6.2.1. BP2-Type with a Heterogeneous Assortment of Large Objects.- 6.2.2. BP2-Type with a Homogeneous Assortment of Large Objects.- 6.3. Actual Bin Packing Problems.- 7 Cutting Stock Types (CS).- 7.1. One-dimensional Cutting Stock Types (CS1).- 7.1.1. CS1-Type with Continuous Quantity Measurement of Large Objects.- 7.1.2. CS1-Types with Discrete Quantity Measurement of Large Objects.- 7.1.2.1. Discrete CSl-Type with a Homogeneous Assortment of Large Objects.- 7.1.2.2. Discrete CSl-Type with a Heterogeneous Assortment of Large Objects.- 7.2. Two-dimensional Cutting Stock Types (CS2).- 7.2.1. CS2-Type with Non-rectangular Small Items.- 7.2.2. CS2-Types with Rectangular Small Items.- 7.2.2.1. Rectangular CS2-Types with Only One Large Object per Figure.- 7.2.2.2. Rectangular CS2-Types with Guillotine Patterns.- 7.2.2.3. Rectangular CS2-Type with Nested Patterns.- 7.3. Three-dimensional Cutting Stock Type (CS3).- 7.4. Actual Cutting Stock Problems.- 8 Knapsack Types (KS).- 8.1. One-dimensional Knapsack Type (KS1).- 8.2. Two-dimensional Knapsack Type (KS2).- 8.3. Three-dimensional Knapsack Type (KS3).- 8.4. Actual Knapsack Problems.- 9 Pallet Loading Types (PL).- 9.1. Two-dimensional Pallet Loading Type (PL2).- 9.2. Three-dimensional Pallet Loading Type (PL3).- 9.3. Actual Pallet Loading Problems.- 10 Conclusions.- I. A Bibliography of Further C&P-Problems.- A. Published Surveys.- B. Literary References not Closely Analysed.- C. Most Recent Sources.- II. Brief Description of the Characteristics.- III. LARS Data Base System.- List of Abbreviations for the Journals.- I. General Literature.- II. C&P-Literature.
Some of the hardest computational problems have been successfully attacked through the use of probabilistic algorithms, which have an element of randomness to them. Concepts from the field of probability are also increasingly useful in analyzing the performance of algorithms, broadening our understanding beyond that provided by the worst-case or average-case analyses. This book surveys both of these emerging areas on the interface of the mathematical sciences and computer science. It is designed to attract new researchers to this area and provide them with enough background to begin explorations of their own.
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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.
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