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 82
... determine a prior sequence of steps leading to a solution. Search can be performed with either blind strategies or ... determined by the environment of genetic system (the diversity of population) but not by the operator itself. In ...
... determines what particular characteristic the gene represents. At a particular locus, a gene may encode one of several different values of the particular characteristic it represents. The different values of a gene are called alleles ...
... determining the direction of genetic search. The stochastic operators give offspring by altering parents by random numbers with some distribution. 1.2.4.2 Mutation Mutation is a background operator which produces spontaneous random ...
... determine selection probability or survival probability for each chromosome proportional to the fitness value. Then ... determined according to these values. Fitness scaling has a twofold intention: (1) to maintain a reasonable ...
... determined with a set-and-test approach. Since GA is an intrinsically dynamic and adaptive process, the use of constant parameters is in contrast to the general evolutionary spirit. Therefore, it is a natural idea to try to modify the ...
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 |