Multi Objective Fractional Programming by Genetic Algorithm

被引：0

作者：

Roy, Debasish ^{[1
]}

Dasgupta, Rajib ^{[2
]}

机构：

[1] IISWBM, Coll Sq, Kolkata, India

[2] Calcutta Univ, Dept Commerce, Kolkata, W Bengal, India

来源：

2016 SECOND IEEE INTERNATIONAL CONFERENCE ON RESEARCH IN COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (ICRCICN) | 2016年

关键词：

MOOP; Genetic Algorithm; Fractional Programming; DEA; Efficiency;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Efficiency of any system or organization can be dealt as output divided by input. In case an organization has multiple inputs, the effective input can be treated as a linear combination of inputs and similarly output can be treated as a combination of outputs. This ratio of the linear combination of output divided by input is a fraction. Optimization of this multivariable fraction is a mathematical challenge. A system may have multiple such ratios to be optimized, where independent variables are same in all the fractional functions. Though there is a large number of numerical algorithms for solving such an abnormal function, it has been found genetic algorithm performs far better. In this paper a new way of obtaining the Pareto Optimal front for the Multi Objective Optimisation problem consisting of multiple fractions has been demonstrated using Genetic Algorithm implemented in MATLAB.

引用

页码：128 / 134

页数：7