Improved evolutionary algorithm design for the project scheduling problem based on runtime analysis

IEEE Transactions on Software Engineering

Volumn 40, Issue 1, 2014, Pages 83-102

  Minku, Leandro L ^a   Sudholt, Dirk ^b   Yao, Xin ^a  

^a UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^b UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

evolutionary algorithms; runtime analysis; Schedule and organizational issues; search based software engineering; software project management; software project scheduling

Indexed keywords

DESIGN; SCHEDULING; SOFTWARE ENGINEERING;

RUN-TIME ANALYSIS; SCHEDULE AND ORGANIZATIONAL ISSUES; SEARCH-BASED SOFTWARE ENGINEERING; SOFTWARE PROJECT MANAGEMENT; SOFTWARE PROJECT SCHEDULING;

EVOLUTIONARY ALGORITHMS;

EID: 84898619003     PISSN: 00985589     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSE.2013.52     Document Type: Article

References (45)

1. L.L. Minku, D. Sudholt, and X. Yao, "Evolutionary Algorithms for the Project Scheduling Problem: Runtime Analysis and Improved Design," Proc. 14th Int' l Conf. Geneticand Evolutionary Computation Conf. (GECCO 12), pp. 1221-1228, 2012.
2. T.K. Abdel-Hamid and S.E. Madnick, "The Dynamics of Software Project Scheduling," vol. 26, no. 5, pp. 340-346, 1983.
3. I. Sommerville, Software Engineering. Addison-Wesley, 2001.
4. 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, vol. 41, no. 5, pp. 495-519, 2011.
5. C.K. Chang, M.J. Christensen, and T. Zhang, "Genetic Algorithms for Project Management," Annals of Software Eng., vol. 11, pp. 107-139, 2001. (Pubitemid 33634472)
6. E. Alba and J.F. Chicano, "Software Project Management with GAs," Information Sciences, vol. 177, pp. 2380-2401, 2007. (Pubitemid 46435498)
7. F. Luna, D. Gonz-alez-Alvarez, F. Chicano, and M.A. Vega-Rodr-?guez, "On the Scalability of Multi-Objective Metaheuristics for the Software Scheduling Problem," Proc. 11th Int'l Conf. Intelligent System Design and Applications (ISDA '11), pp. 1110-1115, 2011.
8. N. Nan and D. Harter, "Impact of Budget and Schedule Pressure on Software Development Cycle Time and Effort," IEEE Trans. Software Eng., vol. 35, no. 5, pp. 624-637, Sept./Oct. 2009.
9. E. Yourdon, Death March: The Complete Software Developer's Guide to Surviving "Mission Impossible". Prentice Hall PTR, 1997.
10. K.J. Stewart and S. Gosain, "The Impact of Ideology on Effectiveness in Open Source Software Development Teams," MIS Quarterly, vol. 30, no. 2, pp. 291-314, 2006. (Pubitemid 46050493)
11. B. Fitzgerald, "The Transformation of Open Source Software," MIS Quarterly, vol. 30, no. 3, pp. 587-598, 2006. (Pubitemid 46051913)
12. N. Levina and J.W. Ross, "From the Vendor's Perspective: Exploring the Value Proposition in Information Technology Outsourcing," MIS Quarterly, vol. 27, no. 3, pp. 331-364, 2003.
13. B. Ives and S.L. Jarvenpaa, "Applications of Global Information Technology: Key Issues for Management," MIS Quarterly, vol. 15, no. 1, pp. 33-50, 1991.
14. W.-N. Chen and J. Zhang, "Ant Colony Optimization for Software Project Scheduling and Staffing with an Event-Based Scheduler," IEEE Trans. Software Eng., vol. 39, no. 1, pp. 1-17, Jan. 2013.
15. M. Harman, "The Current State and Future of Search Based Software Engineering," Proc. Future of Software Eng., pp. 342-357, 2007. (Pubitemid 47484936)
16. A.E. Eiben and J.E. Smith, Introduction to Evolutionary Computing. Springer-Verlag, 2003.
17. C. Chao, "Spmnet: A New Methodology for Software Management," PhD dissertation, The Univ. of Illinois at Chicago, 1995.
18. P. Kapur, A. Ngo-The, G. Ruhe, and A. Smith, "Optimized Staffing for Product Releases and Its Application at Chartwell Technology," J. Software Maintenance and Evolution: Research and Practice, vol. 20, no. 5, pp. 365-386, 2008.
19. C.K. Chang, H. Jiang, Y. Di, D. Zhu, and Y. Ge, "Time-Line Based Model for Software Project Scheduling with Genetic Algorithms," Information and Software Technology, vol. 50, no. 11, pp. 1142-1154, 2008.
20. F. Chicano, F. Luna, A. J. Nebro, and E. Alba, "Using Multi-Objective Metaheuristics to Solve the Software Project Scheduling Problem," Proc. 13th Ann. Geneticand Evolutionary Computation Conf. (GECCO '11), ACM, pp. 1915-1922, 2011.
21. S. Gueorguiev, M. Harman, and G. Antoniol, "Software Project Planning for Robustness and Completion Time in the Presence of Uncertainty Using Multi Objective Search Based Software Engineering," Proc. 11th Ann. Geneticand Evolutionary Computation (GECCO '09), pp. 1673-1680, 2009.
22. J. Ren, M. Harman, and M. Penta, "Cooperative Co-Evolutionary Optimization of Software Project Staff Assignments and Job Scheduling," Proc. Third Int'l Conf. Search Based Software Eng., vol. 6956, pp. 127-141, 2011.
23. B. Boehm, Software Engineering Economics. Prentice-Hall, 1981.
24. M. Shepperd and C. Schofield, "Estimating Software Project Effort Using Analogies," IEEE Trans. Software Eng., vol. 23, no. 12, pp. 736-743, Nov. 1997. (Pubitemid 127762233)
25. S. Chulani, B. Bohem, and B. Steece, "Bayesian Analysis of Empirical Software Engineering Cost Models," IEEE Trans. Software Eng., vol. 25, no. 4, pp. 573-583, July/Aug. 1999. (Pubitemid 129304119)
26. B. Boehm, C. Abts, A.W. Brown, S. Chulani, B.K. Clark, E. Horowitz, R. Madachy, D.J. Reifer, and B. Steece, Software Cost Estimation with COCOMO II. Prentice-Hall, 2000.
27. E. Kocaguneli, T. Menzies, A. Bener, and J.W. Keung, "Exploiting the Essential Assumptions of Analogy-Based Effort Estimation," IEEE Trans. Software Eng., vol. 38, no. 2, pp. 425-438, Mar./Apr. 2012.
28. L.L. Minku and X. Yao, "Software Effort Estimation as a Multi-Objective Learning Problem," ACM Trans. Software Eng. Methodology, vol. 22, no. 4, p. 32, 2013.
29. L.A. Maciaszek and B.L. Liong, Practical Software Engineering-A Case Study Approach. Addison-Wesley, 2005.
30. A. Barreto, M. de O. Barros, and C. Werner, "Staffing a Software Project: A Constraint Satisfaction and Optimization-Based Approach," Computers & Operations Research, vol. 35, pp. 3073-3089, 2008. (Pubitemid 351335137)
31. R. Kolisch and S. Hartmann, "Experimental Investigation of Heuristics for Resource-Constrained Project Scheduling: An Update," European J. Operational Research, vol. 174, no. 1, pp. 23-37, 2006. (Pubitemid 44866841)
32. S. Droste, T. Jansen, and I. Wegener, "On the Analysis of the 1 \+ 1 Evolutionary Algorithm," Theoretical Computer Science, vol. 276, no. 1/2, pp. 51-81, 2002.
33. P.S. Oliveto, J. He, and X. Yao, "Time Complexity of Evolutionary Algorithms for Combinatorial Optimization: A Decade of Results," Int'l J. Automation and Computing, vol. 4, no. 3, pp. 281-293, 2007. (Pubitemid 47167355)
34. F. Neumann and C. Witt, Bioinspired Computation in Combinatorial Optimization-Algorithms and Their Computational Complexity. Springer, 2010.
35. Theory of Randomized Search Heuristics-Foundations and Recent Developments, vol. 1, A. Auger, B. Doerr, eds. World Scientific, 2011.
36. D. Sudholt, "A New Method for Lower Bounds on the Running Time of Evolutionary Algorithms," IEEE Trans. Evolutionary Computation, vol. 17, no. 3, pp. 418-435, June 2013.
37. T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein, Introduction to Algorithms, second ed. MIT Press, 2001.
38. B. Doerr, D. Sudholt, and C. Witt, "When Do Evolutionary Algorithms Optimize Separable Functions in Parallel?" Proc. 12th Workshop Foundations of Genetic Algorithms (FOGA 2013), pp. 51-64, 2013.
39. B. Doerr, T. Jansen, D. Sudholt, C. Winzen, and C. Zarges, "Mutation Rate Matters Even When Optimizing Monotonic Functions," Evolutionary Computation, vol. 21, no. 1, pp. 1-21, 2013.
40. M. Lukasiewycz, M. Glaß, F. Reimann, and J. Teich, "Opt4J-A Modular Framework for Meta-Heuristic Optimization," Proc. Genetic and Evolutionary Computing Conf. (GECCO '11), pp. 1723-1730, 2011.
41. A. Agresti and B. Coull, "Approximate Is Better than 'Exact' for Interval Estimation of Binomial Proportions," The Am. Statistician, vol. 52, pp. 119-126, 1998.
42. J. Dem-sar, "Statistical Comparisons of Classifiers over Multiple Data Sets," J. Machine Learning Research, vol. 7, pp. 1-30, 2006. (Pubitemid 43022939)
43. H. Hoos and T. Stutzle, "Local Search Algorithms for SAT: An Empirical Evaluation," J. Automated Reasoning, vol. 24, no. 4, pp. 421-481, 2000.
44. D. Barrero, B. Casta~no, M. R-Moreno, and D. Camacho, "Statistical Distribution of Generation-to-Success in GP: Application to Model Accumulated Success Probability," Proc. 14th European Conf. Genetic Programming (EuroGP '11), pp. 155-166, 2011.
45. R. Motwani and P. Raghavan, Randomized Algorithms. Cambridge Univ. Press, 1995.