Interactive Evolutionary Algorithms for Multi-Objective Optimization

Name: Interactive Evolutionary Algorithms for Multi-Objective Optimization
Brand: VDM Verlag Dr. Mueller E.K.
SKU: 9783639015287
Price: 329.99 RON
Availability: InStock

Design and Validation of a Hybrid Interactive Reference Point Method

Autor: Madan Sathe

Limbă:

Legare: Carte broșată

Editura: VDM Verlag Dr. Mueller E.K.

Disponibilitate: În depozitul extern

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329.99 lei

Many real world problems have conflicting multiple objectiveswhich a decision maker would like to op...

Informații despre carte

Autor

Madan Sathe

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2008

Pagini

124

EAN

9783639015287

ISBN

3639015282

Enbook ID

06811508

Editura

VDM Verlag Dr. Mueller E.K.

Greutate

177

Dimensiuni

152 x 229 x 7

Descriere completă

Many real world problems have conflicting multiple objectiveswhich a decision maker would like to optimize simultaneously. Thus,the decisionmaker may obtain many optimal solutions from asolution method. Subsequently, the user has the difficult task topick one solution. Interactive methods focus on solutions which arelocated in the users region of interest. The author, Madan Sathe,analyses and classifies essential existing interactive classicalmethods and provides a new grouping approach for existinginteractive evolutionary methods. After a crossfertilization ofthese two fields a new Hybrid Interactive Reference Point Method isdesigned and implemented within a powerful graphical tool. The toolguides the user to new regions of interest step by step whileyielding detailed information about solutions at each step.Finally, the new approach is validated on test and real worldproblems. Currently, the scope of the tool is limited to non-linearoptimization problems. The book is aimed at people who areinterested in the field of multi-objective optimization and whowould like to gain information about interactive methods and therealization in graphical tools.

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Interactive Evolutionary Algorithms for Multi-Objective Optimization

Design and Validation of a Hybrid Interactive Reference Point Method

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