Evolutionary Multi-objective optimization Algorithm for Software Modeling

Authors

  • 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

Keywords:

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

Abstract

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.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-02-28

Issue

Volume 3, Issue 2, January-February-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
P. Sireesha, M. Sarada, " Evolutionary Multi-objective optimization Algorithm for Software Modeling, IInternational 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.