Multi-Criteria Website Optimization Using Multi-Objective Quantum Inspired Genetic Algorithm

被引:0
|
作者
Dilip, Kumar [1 ]
机构
[1] Jawaharlal Nehru Univ, Sch Comp & Syst Sci, New Delhi, India
来源
2015 1ST INTERNATIONAL CONFERENCE ON NEXT GENERATION COMPUTING TECHNOLOGIES (NGCT) | 2015年
关键词
Quality check; Qualtrics; Data quality; Survey programming; Online survey; qsf; Qualtrics survey file;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
One of the important impact made by the ever expanding world of Internet is the overwhelming popularity of the online market. Myriad of users are opting for online shopping and numerous websites are getting launched. In order to flourish in such a stiff competitive online world, organizations are paying special attention to develop an effective and efficient website. The website needs to address many issues like, attracting new users, providing easier navigation and increased transaction on the website, among others. Acquiring such website needs to optimize the several underlying criteria simultaneously. These criteria include lower waiting time, attractive presentation of website and increased selling of product or services, among others. The handling of multiple criteria simultaneously makes this task a typical multi-criteria optimization. In this paper a multi-criteria quantum inspired genetic algorithm has been proposed for website optimization considering several criteria simultaneously. Quantum inspired genetic algorithm applies the laws of quantum mechanics and use the q-bit representation, which provides more efficient means for optimization. The multi-objective quantum genetic algorithm is able to provide better trade-off solutions than its classical counterparts, such as genetic algorithm, for considered multi-criteria website optimization problem.
引用
收藏
页码:965 / 970
页数:6
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