TY - BOOK AU - Gen,Mitsuo AU - Cheng,Runwei AU - Lin,Lin ED - SpringerLink (Online service) TI - Network Models and Optimization: Multiobjective Genetic Algorithm Approach T2 - Decision Engineering, SN - 9781848001817 AV - TA177.4-185 U1 - 658.5 23 PY - 2008/// CY - London PB - Springer London KW - Engineering KW - Computer software KW - Combinatorics KW - Engineering economy KW - Engineering Economics, Organization, Logistics, Marketing KW - Operations Research/Decision Theory KW - Algorithm Analysis and Problem Complexity N1 - Multiobjective Genetic Algorithms -- Basic Network Models -- Logistics Network Models -- Communication Network Models -- Advanced Planning and Scheduling Models -- Project Scheduling Models -- Assembly Line Balancing Models -- Tasks Scheduling Models -- Advanced Network Models N2 - Network 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 UR - http://dx.doi.org/10.1007/978-1-84800-181-7 ER -