Evolutionary Multi-objective optimization Algorithm for Software Modeling

Authors(2) :-P. Sireesha, M. Sarada

In this paper, we propose the use of preference-based evolutionary multi-objective optimization techniques (P-EMO) to address different software demonstrating challenges. P-EMO permits the fuse of decision maker (i.e., designer) preferences (e.g., quality, rightness, and so forth.) in multi-objective optimization methods by confining the Pareto front to a locale of intrigue facilitating the basic leadership errand. We examine the extraordinary difficulties and potential advantages of P-EMO in software modeling. We report investigates the utilization of P-EMO on an understood modeling issue where extremely encouraging outcomes are obtained.

Authors and Affiliations

P. Sireesha
PG Student, Department of MCA, St. Ann's College of Engineering & Technology, Chirala, Andhra Pradesh, India
M. Sarada
Assistant Professor, Department of MCA, St. Ann's College of Engineering & Technology, Chirala, Andhra Pradesh, India

Search-Based Software Engineering, User-Preferences, Multi-Objective Optimization, Evolutionary Computation, Modeling.

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Publication Details

Published in : Volume 3 | Issue 2 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 166-173
Manuscript Number : CSEIT1831473
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

P. Sireesha, M. Sarada, "Evolutionary Multi-objective optimization Algorithm for Software Modeling", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 2, pp.166-173, January-February.2018
URL : http://ijsrcseit.com/CSEIT1831473

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