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. |
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... planning and scheduling models, project scheduling models, assembly line balancing models, tasks scheduling models, and advanced network models. Since early 1993, we have devoted our efforts to the research of genetic algorithms and its ...
... .....................................291 5 Advanced Planning and Scheduling Models .......................297 5.1 Introduction ...............................................297 5.2 Job-shopSchedulingModel..................
... , 49]. Multiple objective problems arise in the design, modeling, and planning Fig. 1.10 Membership function for pM Fig. 1.11 Membership function 1.4 Multiobjective Genetic Algorithms 25 MultiobjectiveGeneticAlgorithms.
... planning: How to determine the route road that have prohibitive weight restriction so that the driver can reach the destination within the shortest possible time. 2. Salesperson routing: Suppose that a sales person want to go to Los ...
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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 |