Enhanced GA & LS for Optimizing Soft Constrained Combinatorial Problems


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  • Product Description

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.

Product Specifications
SKU :COC75393
AuthorM. Nandhini and S. Kanmani
Number of Pages136
Publishing Year2014-06-05T00:00:00.000
Edition1 st
Book TypeComputing & information technology
Country of ManufactureIndia
Product BrandScholars' Press
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-10-08 00:00:00
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