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 79
... graph the multiple objective problem in both decision space and criterion space. S is used to denote the feasible region in the decision space and Z is used to denote the feasible region in the criterion space Z={z∈Rq|z1=f1(x),z2 = f2 ...
... graph theory and combinatorial optimization. A lot of optimization problems in network design arose directly from everyday practice in engineering and management: determining shortest or most reliable paths in traffic or communication ...
... graph G =(N,A) is given, and it is a structure consisting of a finite set N of elements called nodes and a set A of unordered pairs of nodes called arcs. The descriptions of the models are as follows. 2.1.1. Shortest. Path. Model: Node.
... graph remains connected. For what subset of arcs is the sum of the arc lengths minimized? Spanning tree models play a central role within the field of network design. It generally arises in one of two ways, directly or indirectly. In ...
... graph (or digraph) G on the nodes set N = {1,2,···,n} is specified by: 1. Its number of nodes n; 2. The list of its arcs, given as a sequence of ordered m pairs A={(i,j), (k,l), ···, (s,t)}. The digraph G of Fig. 2.2 may then be given ...
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 |