The software project scheduling problem: A scalability analysis of multi-objective metaheuristics

Applied Soft Computing Journal

Volumn 15, Issue , 2014, Pages 136-148

  Luna, Francisco ^a   González Álvarez, David L ^a   Chicano, Francisco ^b   Vega Rodríguez, Miguel A ^a  

^a UNIVERSITY OF EXTREMADURA   (Spain)

^b UNIVERSITY OF MÁLAGA   (Spain)

Author keywords

Multi objective optimization; Scalability analysis; Software project scheduling

Indexed keywords

COMPUTER AIDED TECHNIQUE; MULTI OBJECTIVE ALGORITHM; MULTI-OBJECTIVE METAHEURISTICS; SCALABILITY ANALYSIS; SCHEDULING SOFTWARE; SOFTWARE DEVELOPMENT PROCESS; SOFTWARE INDUSTRY; SOFTWARE PROJECT SCHEDULING;

ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION; SCALABILITY; SOFTWARE ENGINEERING;

SCHEDULING;

EID: 84889641311     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2013.10.015     Document Type: Article

References (30)

1. B.W. Boehm, C. Abts, A.W. Brown, S. Chulani, B.K. Clark, E. Harrowitz, R.J. Madachy, D.J. Reifer, and B. Steece Software Cost Estimation with Cocomo II 1st ed. 2000 Prentice Hall PTR Upper Saddle River, NJ, USA
2. P. Brucker, A. Drexl, R. Mohring, K. Neumann, and E. Pesch Resource-constrained project scheduling: notation, classification, models, and methods European Journal of Operational Research 112 1 1999 3 41
3. C.K. Chang, and M. Christensen A net practice for software project management IEEE Software 16 6 1999 80 88 (Pubitemid 30514443)
4. A. Barreto, M. Barros, and C.M.L. Werner Staffing a software project: a constraint satisfaction and optimization-based approach Computer and Opererations Research 35 10 2008 3073 3089 (Pubitemid 351335137)
5. E. Alba, and F. Chicano Software project management with GAs Information Sciences 177 11 2007 2380 2401 (Pubitemid 46435498)
6. G. Antoniol, M.D. Penta, and M. Harman Search-based techniques applied to optimization of project planning for a massive maintenance project 21st IEEE International Conference on Software Maintenance (ICSM 2005) 2005 240 249
7. M. di Penta, M. Harman, and G. Antoniol The use of search-based optimization techniques to schedule and staff software projects: an approach and an empirical study Software - Practice and Experience 41 5 2011 495 519
8. C. Blum, and A. Roli Metaheuristics in combinatorial optimization: overview and conceptual comparison ACM Computing Surveys 35 3 2003 268 308
9. M. Harman, S.A. Mansouri, and Y. Zhang Search-based software engineering: trends, techniques and applications ACM Computing Surveys 45 1 2012 11
10. J.F. Chicano, F. Luna, A.J. Nebro, and E. Alba Using multi-objective metaheuristics to solve the software project scheduling problem Proceedings of GECCO 2011 1915 1922
11. K. Deb Multi-objective Optimization Using Evolutionary Algorithms 2001 John Wiley & Sons Chichester, UK
12. C.A. Coello Coello, G.B. Lamont, and D.A. Van Veldhuizen Evolutionary Algorithms for Solving Multi-Objective Problems 2nd ed. 2007 Springer New York
13. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan A fast and elitist multiobjective genetic algorithm: NSGA-II IEEE Transactions on Evolutionary Computation 6 2 2002 182 197 (Pubitemid 34555372)
14. E. Zitzler, M. Laumanns, and L. Thiele SPEA2: improving the strength Pareto evolutionary algorithms EUROGEN 2001 2002 95 100
15. J. Knowles, and D. Corne Approximating the nondominated front using the Pareto archived evolution strategy Evolutionary Computation 8 2 2000 149 172
16. A. Rubio-Largo, M.A. Vega-Rodríguez, J.A. Gómez-Pulido, and J.M. Sánchez-Pérez A differential evolution with Pareto tournaments for solving the routing and wavelength assignment problem in WDM networks 2010 IEEE Congress on Evolutionary Computation (CEC) 2010 129 136
17. X.-S. Yang Firefly algorithms for multimodal optimization 5th International Symposium of Stochastic Algorithms: Foundations and Applications (SAGA'09), Vol. 5792 2009 169 178
18. D. Karaboga An idea based on honey bee swarm for numerical optimization, Tech. Rep. tr06 2005 Erciyes University Turkey
19. A.J. Nebro, J.J. Durillo, F. Luna, B. Dorronsoro, E. Alba, and Mocell A cellular genetic algorithm for multiobjective optimization International Journal of Intelligent Systems 24 7 2009 726 746
20. S. Kukkonen, and J. Lampinen GDE3: the third evolution step of generalized differential evolution IEEE CEC'05 2005 443 450 (Pubitemid 41495887)
21. E. Zitzler, and L. Thiele Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach IEEE Transactions on Evolutionary Computation 3 4 1999 257 271 (Pubitemid 30544879)
22. J. Knowles A summary-attainment-surface plotting method for visualizing the performance of stochastic multiobjective optimizers 5th Int. Conf. on Intelligent Systems Design and Applications (ISDA'05) 2005 552 557
23. F. Luna, D.L. González-Álvarez, F. Chicano, and M.A. Vega-Rodríguez On the scalability of multi-objective metaheuristics for the software scheduling problem Proceedings of the 11th International Conference on Intelligent Systems Design and Applications (ISDA'11) 2011 IEEE Computer Society 1110 1115
24. K. Price, and R. Storn Differential evolution - a simple evolution strategy for fast optimization Dr. Dobb's Journal 22 4 1997 18-24 and 78
25. A.J. Nebro, J.J. Durillo, F. Luna, B. Dorronsoro, and E. Alba Design issues in a multiobjective cellular genetic algorithm EMO 2007, Vol. LNCS 4403 2007 126 140 (Pubitemid 350270882)
26. J. Lampinen DE's selection rule for multiobjective optimization, Tech. rep. 2001 Lappeenranta University of Technology, Department of Information Technology http://www.it.lut.fi/kurssit/03-04/010778000/MODE.pdf
27. A. Jaszkiewicz A comparative study of multiple-objective metaheuristics on the bi-objective set covering problem and the Pareto memetic algorithm Annals of Operations Research 131 1-4 2004 135 158 (Pubitemid 39195941)
28. A. Jaszkiewicz On the computational efficiency of multiple objective metaheuristics. the knapsack problem case study European Journal of Operational Research 158 2 2004 148 433
29. S. García, D. Molina, M. Lozano, and F. Herrera A study on the use of non-parametric tests for analyzing the evolutionary algorithms behaviour: a case study on the CEC2005 special session on real parameter optimization Journal of Heuristics 15 6 2009 617 644
30. D.J. Sheskin Handbook of Parametric and Nonparametric Statistical Procedures 4th ed. 2007 Chapman & Hall/CRC London, UK