Network Models and Optimization: Multiobjective Genetic Algorithm ApproachNetwork models are critical tools in business, management, science and industry. Network Models and Optimization: Multiobjective Genetic Algorithm Approach 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. Network Models and Optimization: Multiobjective Genetic Algorithm Approach extensively covers algorithms and applications, including shortest path problems, minimum cost flow problems, maximum flow problems, minimum spanning tree problems, travelling 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. Network Models and Optimization: Multiobjective Genetic Algorithm Approach can be used both as a student textbook and as a professional reference for practitioners in many disciplines who use network optimization methods to model and solve problems. |
From inside the book
Results 1-5 of 63
... of IEE Japan in 2005 with Dr. Osamu Katai, Dr. Hiroshi Kawakami and Dr. Ya- suhiro Tsujimura. All of these conferences/workshops/committees are continuing right now to develop our research topics with face to vi Preface.
... develop our research topics with face to face contact. Dr. Gen called on additional conference, ANNIE2008 (Artificial Neural Networks in Engineering; Intelligent Systems Design: Neural Networks, Fuzzy Logic, Evolutionary Computation ...
... develop, the crossover operator provides exploration in the neighborhood of each of them. In other words, what kinds of searches (exploitation or exploration) a crossover performs would be determined by the environment of genetic system ...
... developed this method to self-adapt the mutation step size and the mutation rotation angles in evolution strategies [5]. Hinterding used a multi-chromosome to implement the self-adaptation in the cutting stock problem with contiguity ...
... developed during the past two decades. One of special issues in multiobjective optimization problems is the fitness assignment mechanism. Since the 1980s, several fitness assignment mechanisms have been proposed and applied in ...
Contents
1 | |
49 | |
Logistics Network Models | 135 |
Communication Network Models | 229 |
Advanced Planning and Scheduling Models | 297 |
Project Scheduling Models | 419 |
Assembly Line Balancing Models | 477 |
Tasks Scheduling Models | 551 |
References | 604 |
Index | 687 |
Other editions - View all
Network Models and Optimization: Multiobjective Genetic Algorithm Approach Mitsuo Gen,Runwei Cheng,Lin Lin No preview available - 2008 |
Network Models and Optimization: Multiobjective Genetic Algorithm Approach Mitsuo Gen,Runwei Cheng,Lin Lin No preview available - 2010 |