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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... determine the direction and/or magnitude of the change to the strategy parameter. Early examples of this kind of adaptation include Rechenberg's “1/5 success rule” in volution strategies, which was used to vary the step size of mutation ...
... determined as n(t)=int ( ̄n+D− 2D T−1 ( t −T ·int ( t−1 T ) −1 )) The Koumousis and Katsaras proposed stGA utilizes ... determine the exploitation– exploration trade-off on the search space. All of genetic parameters should be auto ...
... determines the weight of exploration for the search space. Immigration Operator: Moed et al. [47] proposed an immigration ... determine the weight of exploitation for the search space. The main scheme is to use two FLCs: auto-tuning for ...
... determine the route? 3. Investment planning: How to determine the invest strategy to get an optimal investment plan. 4. Message routing in communication systems: The routing algorithm computes the shortest (least cost) path between the ...
... instance after a finite number of steps. 4. Determinism: The sequence of steps has to be uniquely determined for each instance. Of course, an algorithm should also be correct, that is, 54 2 Basic Network Models AlgorithmsandComplexity.
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 |