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 73
... Trees, IEEE Transactions on Evolutionary Computation, 7(3), 225–239. 26. Kim, J. H. & Myung, H. (1996). A two-phase evolutionary programming for general constrained optimization problem, Proceeding of the 1st Annual Conference on ...
... tree models (i.e., arc selection) and maximum flow models (i.e., arc selection and flow assignment) etc. These network models are used most extensively in applica- Network Design Models Shortest Path Model (SPP) Minimum Spanning Tree 49 ...
... Tree Model (MST) Bicriteria SPP (bSPP) Maximum Flow Model (MXF) Capacitated MST (cMST) Degree-constrained MST(dMST) Multicriteria MST (mMST) Minimum Cost Flow Model (MCF) Bicriteria MXF/MCF Model Fig. 2.1 The core models of network ...
... tree objective (sum of arc costs), or (2) the problem itself bears little resemblance to an “optimal tree” problem – in these instances, we often need to be creative in modeling the problem so that it becomes a minimum spanning tree ...
... tree and deleting tree arcs one by one in nonincreasing order of their lengths. Cluster analysis is important in a variety of disciplines that rely on empirical investigations. 2.1.3. Maximum. Flow. Model: Arc. Selection. and. Flow.
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 |