: Mitsuo Gen, Runwei Cheng, Lin
: Network Models and Optimization Multiobjective Genetic Algorithm Approach
: Springer-Verlag
: 9781848001817
: 1
: CHF 199.40
:
: Allgemeines, Lexika
: English
: 692
: Wasserzeichen/DRM
: PC/MAC/eReader/Tablet
: PDF

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.

Preface6
Contents10
1 Multiobjective Genetic Algorithms16
1.1 Introduction16
1.2 Implementation of Genetic Algorithms20
1.3 Hybrid Genetic Algorithms30
1.4 Multiobjective Genetic Algorithms40
References59
2 Basic Network Models64
2.1 Introduction64
2.2 Shortest Path Model72
2.3 Minimum Spanning Tree Models94
2.4 Maximum Flow Model111
2.5 Minimum Cost Flow Model122
2.6 Bicriteria MXF/MCF Model130
2.7 Summary143
References145
3 Logistics Network Models150
3.1 Introduction150
3.2 Basic Logistics Models154
3.3 Location Allocation Models169
3.4 Multi-stage Logistics Models190
3.5 Flexible Logistics Model208
3.6 Integrated Logistics Model with Multi-time Period and Inventory223
3.7 Summary237
References240
4 Communication Network Models244
4.1 Introduction244
4.2 Centralized Network Models249
4.3 Backbone Network Model261
4.4 Reliable Network Models272
4.5 Summary305
References306
5 Advanced Planning and Scheduling Models312
5.1 Introduction312
5.2 Job-shop Scheduling Model318
5.3 Flexible Job-shop Scheduling Model352
5.4 Integrated Operation Sequence and Resource Selection Model370
5.5 Integrated Scheduling Model with Multi-plant391
5.6 Manufacturing and Logistics Model with Pickup and Delivery410
5.7 Summary427
References427
6 Project Scheduling Models434
6.1 Introduction434
6.2 Resource-constrained Project Scheduling Model436
6.3 Resource-constrained Multiple Project Scheduling Model453
6.4 Resource-constrained Project Scheduling Model with Multiple Modes472
6.5 Summary487
References488
7 Assembly Line Balancing Models492
7.1 Introduction492
7.2 Simple Assembly Line Balancing Model495
7.3 U-shaped Assembly Line Balancing Model508
7.4 Robotic Assembly Line Balancing Model520
7.5 Mixed-model Assembly Line Balancing Model541
7.6 Summary561
References561
8 Tasks Scheduling Models566
8.1 Introduction566
8.2 Continuous Task Scheduling577
8.3 Real-time Task Scheduling in Homogeneous Multiprocessor598
8.4 Real-time Task Scheduling in Heterogeneous Multiprocessor System610
8.5 Summary617
References619
9 Advanced Network Models622
9.1 Airline Fleet Assignment Models622
9.2 Container Terminal Network Model651
9.3 AGV Dispatching Model666
9.4 Car Navigation Routing Model681
9.5 Summary696
References697
Index702