Gen / Cheng / Lin Network Models and Optimization

Multiobjective Genetic Algorithm Approach
1. Auflage 2008
ISBN: 978-1-84800-181-7
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 692 Seiten

Reihe: Decision Engineering

Network models are critical tools in business, management, science and industry. 'Network Models and Optimization' presents an insightful, comprehensive, and up-to-date treatment of multiple objective genetic algorithms to network optimization problems in many disciplines, such as engineering, computer science, operations research, transportation, telecommunication, and manufacturing. The book extensively covers algorithms and applications, including shortest path problems, minimum cost flow problems, maximum flow problems, minimum spanning tree problems, traveling salesman and postman problems, location-allocation problems, project scheduling problems, multistage-based scheduling problems, logistics network problems, communication network problem, and network models in assembly line balancing problems, and airline fleet assignment problems. The book can be used both as a student textbook and as a professional reference for practitioners who use network optimization methods to model and solve problems.

Professor Mitsuo Gen is currently a professor of the Graduate School of Information, Production and Systems at Waseda University. He previously worked as a lecturer and professor at Ashikaga Institute of Technology. His research interests include genetic and evolutionary computation; fuzzy logic and neural networks; supply chain network design; optimization for information networks; and advanced planning and scheduling (APS). Runwei Cheng is a Doctor of Engineering and currently works for JANA Solutions, Inc. Lin Lin is currently a PhD candidate and research assistant at Waseda University, where he gained his MSc from the Graduate School of Information, Production and Systems. His research interests include hybrid genetic algorthims; neural networks; engineering optimization; multiobjective optimization; applications of evolutionary techniques; production and logistics; communication networks; image processing and pattern recognition; and parallel and distributed systems.

Autoren/Hrsg.

Gen, Mitsuo

Cheng, Runwei

Lin, Lin

Inhaltsverzeichnis

1;Preface;6
2;Contents;10
3;1 Multiobjective Genetic Algorithms;16
3.1;1.1 Introduction;16
3.2;1.2 Implementation of Genetic Algorithms;20
3.3;1.3 Hybrid Genetic Algorithms;30
3.4;1.4 Multiobjective Genetic Algorithms;40
3.5;References;59
4;2 Basic Network Models;64
4.1;2.1 Introduction;64
4.2;2.2 Shortest Path Model;72
4.3;2.3 Minimum Spanning Tree Models;94
4.4;2.4 Maximum Flow Model;111
4.5;2.5 Minimum Cost Flow Model;122
4.6;2.6 Bicriteria MXF/MCF Model;130
4.7;2.7 Summary;143
4.8;References;145
5;3 Logistics Network Models;150
5.1;3.1 Introduction;150
5.2;3.2 Basic Logistics Models;154
5.3;3.3 Location Allocation Models;169
5.4;3.4 Multi-stage Logistics Models;190
5.5;3.5 Flexible Logistics Model;208
5.6;3.6 Integrated Logistics Model with Multi-time Period and Inventory;223
5.7;3.7 Summary;237
5.8;References;240
6;4 Communication Network Models;244
6.1;4.1 Introduction;244
6.2;4.2 Centralized Network Models;249
6.3;4.3 Backbone Network Model;261
6.4;4.4 Reliable Network Models;272
6.5;4.5 Summary;305
6.6;References;306
7;5 Advanced Planning and Scheduling Models;312
7.1;5.1 Introduction;312
7.2;5.2 Job-shop Scheduling Model;318
7.3;5.3 Flexible Job-shop Scheduling Model;352
7.4;5.4 Integrated Operation Sequence and Resource Selection Model;370
7.5;5.5 Integrated Scheduling Model with Multi-plant;391
7.6;5.6 Manufacturing and Logistics Model with Pickup and Delivery;410
7.7;5.7 Summary;427
7.8;References;427
8;6 Project Scheduling Models;434
8.1;6.1 Introduction;434
8.2;6.2 Resource-constrained Project Scheduling Model;436
8.3;6.3 Resource-constrained Multiple Project Scheduling Model;453
8.4;6.4 Resource-constrained Project Scheduling Model with Multiple Modes;472
8.5;6.5 Summary;487
8.6;References;488
9;7 Assembly Line Balancing Models;492
9.1;7.1 Introduction;492
9.2;7.2 Simple Assembly Line Balancing Model;495
9.3;7.3 U-shaped Assembly Line Balancing Model;508
9.4;7.4 Robotic Assembly Line Balancing Model;520
9.5;7.5 Mixed-model Assembly Line Balancing Model;541
9.6;7.6 Summary;561
9.7;References;561
10;8 Tasks Scheduling Models;566
10.1;8.1 Introduction;566
10.2;8.2 Continuous Task Scheduling;577
10.3;8.3 Real-time Task Scheduling in Homogeneous Multiprocessor;598
10.4;8.4 Real-time Task Scheduling in Heterogeneous Multiprocessor System;610
10.5;8.5 Summary;617
10.6;References;619
11;9 Advanced Network Models;622
11.1;9.1 Airline Fleet Assignment Models;622
11.2;9.2 Container Terminal Network Model;651
11.3;9.3 AGV Dispatching Model;666
11.4;9.4 Car Navigation Routing Model;681
11.5;9.5 Summary;696
11.6;References;697
12;Index;702