Enhanced Ga & Ls for Optimizing Soft Constrained Combinatorial Problems

Nandhini, M.; Kanmani, S.

ISBN 10: 3639710819 ISBN 13: 9783639710816

Editorial: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2014

Idioma: Ingl�s

Nuevos Condici�n: New Encuadernaci�n de tapa blanda

Guardar para m�s tarde

Vendido por Books Puddle, New York, NY, Estados Unidos de America

Vendedor de AbeBooks desde 22 de noviembre de 2018

Calificaci�n del vendedor: 4 de 5 estrellas

Ver los art�culos de este vendedor

Ver todos los ejemplares de este libro

Nuevos - Encuadernaci�n de tapa blanda

Condici�n: New

Precio: EUR 90,74 Convertir moneda

EUR 9,76 gastos de env�o desde Estados Unidos de America a Espa�a Destinos, gastos y plazos de env�o

Cantidad disponible: 4 disponibles

A�adir al carrito

Guardar para m�s tarde

Descripci�n

pp. 136.

N� de ref. del art�culo 26128169590

Contactar al vendedor

Denunciar este art�culo

Detalles bibliogr�ficos

T�tulo: Enhanced Ga & Ls for Optimizing Soft Constrained Combinatorial Problems
Editor: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG
Fecha de publicaci�n: 2014
Idioma: Ingl�s
ISBN 10: 3639710819
ISBN 13: 9783639710816
Encuadernaci�n: Encuadernaci�n de tapa blanda
Estado: New

Acerca de

Sinopsis

To design a model for optimizing Combinatorial Problems(CPs) with multi objectives and multi soft constrained features, a new domain specific crossover and mutation operators in GA are proposed and are combined and hybridized with local search algorithm namely Steepest Ascent Hill Climbing. This resulted to twelve algorithms to optimize CPs with multi objectives. The performance of these twelve algorithms are analysed on two CPs namely College Course Timetabling Problem (CCTP) and Multi Job Shop Scheduling Problem (MJSSP) with the instances of institution based data set for CCTP and standard benchmark instances of MJSSP. From the analysis of these algorithms, the best combination of hybrid model to optimize multi soft constrained CPs with multi objectives is identified.

Rese�a del editor

To design a model for optimizing Combinatorial Problems(CPs) with multi objectives and multi soft constrained features, a new domain specific crossover and mutation operators in GA are proposed and are combined and hybridized with local search algorithm namely Steepest Ascent Hill Climbing. This resulted to twelve algorithms to optimize CPs with multi objectives. The performance of these twelve algorithms are analysed on two CPs namely College Course Timetabling Problem (CCTP) and Multi Job Shop Scheduling Problem (MJSSP) with the instances of institution based data set for CCTP and standard benchmark instances of MJSSP. From the analysis of these algorithms, the best combination of hybrid model to optimize multi soft constrained CPs with multi objectives is identified.

"Sobre este t�tulo" puede pertenecer a otra edici�n de este libro.

Descripci�n de la librer�a

I mainly carry imported books from South East Asia / South Asia for readers of all Age Groups.

Ver la p�gina web de la librer�a

Informaci�n empresarial del vendedor

PLETOS INC
6931 51st Avenue, WOODSIDE, Woodside, NY, 11377, U.S.A.

Condiciones de venta y env�o

Condiciones de venta

We accept return for those books which are received damamged. Though we take appropriate care in packaing to avoid such situation.

Condiciones de env�o

M�todos de pago

A�adir una petici�n