Software requirements selection using quantum-inspired elitist multi-objective evolutionary algorithm

IEEE-International Conference on Advances in Engineering, Science and Management, ICAESM-2012

Volumn , Issue , 2012, Pages 782-787

  Kumari, A Charan ^a   Srinivas, K ^a   Gupta, M P ^b  

^a DAYALBAGH EDUCATIONAL INSTITUTE   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

Author keywords

Multi objective Next Release Problem; Quantum inspired Multi objective Evolutionary Algorithm; Search based software engineering; Software requirements selection

Indexed keywords

BENCH-MARK PROBLEMS; BUSINESS GOALS; CUSTOMER REQUIREMENTS; FASTER CONVERGENCE; MULTI OBJECTIVE; MULTI OBJECTIVE EVOLUTIONARY ALGORITHMS; NP-HARD; OPTIMIZATION TECHNIQUES; PARETO-OPTIMAL FRONT; PROBLEM INSTANCES; QUANTUM COMPUTING; SEARCH-BASED SOFTWARE ENGINEERING; SMALL POPULATION; SOFTWARE PRODUCT DEVELOPMENT; SOFTWARE REQUIREMENTS; TOTAL COSTS;

BENCHMARKING; CUSTOMER SATISFACTION; OPTIMIZATION; POPULATION STATISTICS; QUANTUM COMPUTERS; REQUIREMENTS ENGINEERING; SOFTWARE ENGINEERING;

EVOLUTIONARY ALGORITHMS;

EID: 84863979557     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. Bagnall, A.J., V. J. Rayward-Smith, and I. M. Whittley, 2001. -The next release problem, Information and Software Technology, 43(2001): 883-890.
2. Harman, M., and F. B. Jones., 2001. -Search Based Software Engineering, Information and Software Technology, 43(2001): 833-839.
3. Zhang, Y., M. Harman, and A. S. Mansouri, 2007. -The Multi-Objective Next Release Problem, GECCO '07: proceedings of the 9th annual conference on genetic and evolutionary computation. ACM, New York, pp. 1129-1136.
4. Durillo, J., J., Y. Zhang, E. Alba, A. J. Nebro, 2009. -A study of the multi-objective next release problem, SSBSE '09: proceedings of the 2009 I st international symposium on search based software engineering. IEEE Computer Society, Washington, pp. 49-58.
5. Deb, K., 2001, Multi-Objective Optimi=ation using Evolutionary Algorithms. Wiley Chichester, UK.
6. Carlos A. Coello Coello, Gary B. Lamont and David A. Van Veldhuizen, 2007. Evolutionary Algorithms for solving Multi-Objective Problems. Springer.
7. Han, K. H. and J. H. Kim, 2002. -Quantum-inspired Evolutionary Algorithm for a Class of Combinatorial Optimization, IEEE Transactions on Evolutionary Computation, 6(6): 580-593.
8. Deb, K., A. Pratap, S. Agarwal, and T. Meyarivan., 2002. -A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, 6(2): 182-197.
9. Zitzler E, Thiele L., 1999. -Multiobjective Evolutionary algorithms: A comparative case study and the strength pareto approach, IEEE Transactions on Evolutionary Computation, 3(4) : 257-271.