Intelligent algorithms for packing and cutting problem / / Yunqing Rao, Qiang Luo

• Autore: Rao Yunqing
• Pubblicazione: Gateway East, Singapore : , : Springer, , [2022]; ©2022
• Descrizione fisica: 1 online resource (338 pages)
• Disciplina: 511.64
• Soggetto topico: Cutting stock problem; Cybernetics; Cibernètica
• Soggetto genere / forma: Llibres electrònics
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Intro -- Preface -- Contents -- 1 Introduction to the Packing and Cutting Problem -- 1.1 Problem Definition -- 1.1.1 Packing Problem -- 1.1.2 Cutting Problem -- 1.2 Literature Review -- 1.2.1 Review for 2DRSP -- 1.2.2 Review for 2DISP -- 1.2.3 Review for CSP -- 1.3 Development Trends -- References -- 2 Intelligent Algorithms for Rectangular Packing Problem -- 2.1 Problem Description -- 2.2 Memetic Algorithm for the Problem -- 2.2.1 Introduction -- 2.2.2 The Placement Strategy -- 2.2.3 The Memetic Algorithm -- 2.2.4 Implementation of Memetic Algorithm -- 2.2.5 Experimental Results -- 2.3 Discrete Grey Wolf Optimization -- 2.3.1 Introduction -- 2.3.2 Improved Best-Fit Heuristic Algorithm -- 2.3.3 Discrete Grey Wolf Optimization -- 2.3.4 Experimentation and Results -- 2.4 Conclusions -- References -- 3 Intelligent Algorithms for Irregular Packing Problem -- 3.1 Problem Description -- 3.2 The Geometrical Technique -- 3.3 Memetic Algorithm for the Problem -- 3.3.1 Introduction -- 3.3.2 The Memetic Algorithm -- 3.3.3 The Realization of the Adaptive Memetic Algorithm -- 3.3.4 Experimental Study and Discussions -- 3.4 Beam Search Hybridized with Tabu Search for the Problem -- 3.4.1 Introduction -- 3.4.2 Placement Principle Based on Improved NFP -- 3.4.3 The Hybrid Algorithm for Searching Sequence -- 3.4.4 Experimental Results and Discussions -- 3.5 Biased Genetic Algorithm Hybridized with VNS for the Problem -- 3.5.1 Introduction -- 3.5.2 Placement Method -- 3.5.3 Biased Genetic Algorithm Hybridized with VNS -- 3.5.4 Experimental Results and Discussions -- 3.6 Conclusions -- Appendix -- References -- 4 Novel Algorithms for 2DRSP and 2DISP -- 4.1 Reinforcement Learning Algorithm for 2DRPP -- 4.1.1 Introduction and Problem Description -- 4.1.2 Lowest Centroid Placement Method -- 4.1.3 Sequence Optimization Based on Q-learning. ; 4.1.4 Computational Packing Experiments -- 4.2 Reinforcement Learning Algorithm for 2DIPP -- 4.2.1 Introduction -- 4.2.2 Description of Packing Problem -- 4.2.3 Positioning Strategy Based on BL -- 4.2.4 Sequence Optimization Strategy -- 4.2.5 Computational Experiment -- 4.3 Sequential Transfer-Based PSO for 2DIPP -- 4.3.1 Introduction -- 4.3.2 Novel Positioning Strategy Based on NFP -- 4.3.3 Description of Sequence Transfer -- 4.3.4 Computational Experiments -- References -- 5 Solutions for New Variants of Packing Problem -- 5.1 Knapsack Packing Problem with Defects -- 5.1.1 Introduction and Literature Review -- 5.1.2 Problem Description -- 5.1.3 The Approach for the Problem -- 5.1.4 Numerical Experiments and Conclusions -- 5.2 Irregular Packing Problem with Defects -- 5.2.1 Introduction and Problem Description -- 5.2.2 Literature Review -- 5.2.3 Genetic Algorithm and Grey Wolf Optimization -- 5.2.4 Heuristic Placement Algorithm -- 5.2.5 Computational Results and Conclusions -- 5.3 Rectangular Packing Problem with Divisible Items -- 5.3.1 Introduction and Problem Description -- 5.3.2 Related Work -- 5.3.3 The Heuristic Placement Method -- 5.3.4 Integration with Metaheuristic -- 5.3.5 Numerical Experiments and Conclusions -- Appendix -- References -- 6 Integration of Packing and Cutting -- 6.1 An Integrated Approach on Packing and Cut Planning -- 6.1.1 Introduction -- 6.1.2 The Three-Stage Solution -- 6.1.3 Mathematical Modeling -- 6.1.4 The Solving Approach -- 6.1.5 Computational Experiments and Discussion -- 6.2 An Integrated System for Packing and Cutting-Punching -- 6.2.1 Introduction -- 6.2.2 The Overall Structure -- 6.2.3 The Data Structure of IKBS -- 6.2.4 The Knowledge Base of IKBS -- 6.2.5 Case Study and Discussion -- 6.3 An Integrated System for Packing and Sheet Metal Cutting -- 6.3.1 Introduction -- 6.3.2 The System Overall Structure. ; 6.3.3 Nest Planning -- 6.3.4 CAD/CAPP/CAM -- 6.3.5 Case Study -- References -- 7 Intelligent Algorithms for Cutting Scheduling Problem -- 7.1 Problem Description -- 7.2 Improved Hierarchical Genetic Algorithm for the CSP -- 7.2.1 Introduction -- 7.2.2 Problem Statement and Mathematical Modeling -- 7.2.3 Ant Colony-Hierarchical Genetic Algorithm -- 7.2.4 Computational Experiments -- 7.2.5 Conclusions -- 7.3 Hybrid Genetic Algorithm for the Bi-Objective CSP -- 7.3.1 Introduction -- 7.3.2 Problem Description and Formulation -- 7.3.3 VNSGA III Based on Reference Points -- 7.3.4 Evaluation Metric -- 7.3.5 Experimental Design and Results -- 7.4 GWO Algorithm for the Bi-Objective CSP -- 7.4.1 Introduction -- 7.4.2 Problem Description and Formulation -- 7.4.3 Reference-Point-Based GWO Algorithm -- 7.4.4 Experimental Design and Results -- References -- 8 Application on Laser Cutting of Metal Sheets -- 8.1 Introduction to LaserCAM Software -- 8.1.1 Graphics Module -- 8.1.2 Packing Module -- 8.1.3 Laser Cutting Module -- 8.1.4 NC and Report Module -- 8.2 Case 1: Rectangular Packing and Cutting -- 8.3 Case 2: Irregular Packing and Cutting.
• Titolo autorizzato: Intelligent algorithms for packing and cutting problem
• ISBN: 981-19-5916-1
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996495171003316
• Lo trovi qui: Univ. di Salerno
• Serie: Engineering Applications of Computational Methods