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
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... , Runwei Cheng, Lin Lin. Mitsuo Gen Runwei Cheng Lin Lin i nd Optimizatio ^ Multiobjective Genetic Algorithm Approach £} Springer Decision Engineering Series Editor Professor Rajkumar Roy Department of Enterprise. Front Cover.
... Decision-Making in Engineering Design Yotaro Hatamura Composite Systems Decisions Mark Sh. Levin Intelligent Decision-making Support Systems Jatinder N.D. Gupta, Guisseppi A. Forgionne and Manuel Mora T. Knowledge Acquisition in ...
... Decision Engineering Series ISSN 1619-5736 Preface Network design optimization is basically a fundamental issue in. British Library Cataloguing in Publication Data Gen, Mitsuo, 1944- Network models and optimization : multiobjective ...
... .......................639 9.2.2 Multi-stage Decision-based GA . . ......................643 9.2.3 NumericalExperiment................................646 9.3 AGVDispatchingModel ................................
... decision space with the set S as follows: S = {x∈Rn|gi(x)≤0, i=1,2,...,m,x≥0} (1.10) Without loss of generality ... decision space and criterion space. S is used to denote the feasible region in the decision space and Z is used to ...
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 |