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A Dual-Population Memetic Algorithm for Minimizing Total Cost of Multi-Mode Resource-Constrained Project Scheduling

  • Chen, Zhi-Jie (Department of Industrial Engineering and Management Yuan-Ze University) ;
  • Chyu, Chiuh-Cheng (Department of Industrial Engineering and Management Yuan-Ze University)
  • Received : 2010.02.18
  • Accepted : 2010.05.17
  • Published : 2010.06.01

Abstract

Makespan and cost minimization are two important factors in project investment. This paper considers a multi-mode resource-constrained project scheduling problem with the objective of minimizing costs, subject to a deadline constraint. A number of studies have focused on minimizing makespan or resource availability cost with a specified deadline. This problem assumes a fixed cost for the availability of each renewable resource per period, and the project cost to be minimized is the sum of the variable cost associated with the execution mode of each activity. The presented memetic algorithm (MA) consists of three features: (1) a truncated branch and bound heuristic that serves as effective preprocessing in forming the initial population; (2) a strategy that maintains two populations, which respectively store deadline-feasible and infeasible solutions, enabling the MA to explore quality solutions in a broader resource-feasible space; (3) a repair-and-improvement local search scheme that refines each offspring and updates the two populations. The MA is tested via ProGen generated instances with problem sizes of 18, 20, and 30. The experimental results indicate that the MA performs exceptionally well in both effectiveness and efficiency using the optimal solutions or the current best solutions for the comparison standard.

Keywords

References

  1. Bouleimen, K. and Lecocq, H. (2003) A new efficient simulated annealing algorithm for the resourceconstrained project scheduling problem and its multiple mode version, European Journal of Operational Research, 149(2), 2684-281.
  2. Brucker, P., Drexl, A., Mohring, R., Neumann, K., and Pesch, E. (1999) Resource-constrained project scheduling: Notation, classification, models, and methods, European Journal of Operational Research, 112(1), 3-41. https://doi.org/10.1016/S0377-2217(98)00204-5
  3. Buriol, L., Franca, P. M., and Moscato, P. (2004) A new memetic algorithm for the asymmetric traveling salesman problem, Journal of Heuristics, 10(5), 483-506. https://doi.org/10.1023/B:HEUR.0000045321.59202.52
  4. De Reyck, B. (1998) Scheduling Projects with Generalized Precedence Relations-Exact and Heuristic Procedures, Ph.D. Dissertation, Department of Applied Economics, Katholieke University Leuven.
  5. Demeulemeester, E., De Reyck, B., Foubert, B., Herroeleon, W., and Vanhoucke, M. (1998) New computational results on the discrete time/cost trade-off problem in project networks, Journal of the Operational Research Society, 49(11), 1153-1163. https://doi.org/10.1057/palgrave.jors.2600634
  6. Demeulemeester, E. L., and Herroelen, W. S. (2002) Project scheduling: A Research Handbook, Norwell, MA: Kluwer.
  7. Halman, N., Li, C. L., and Simchi-Levi, D. (2009) Fully polynomial-time approximation schemes for timecost tradeoff problems in series-parallel project networks, Operations Research Letters, 37(4), 239-244.
  8. Hamimes, Y. Y., Lasdon, L. S., and Wismer, D. A. (1971) On a bicriterion formulation of the problems of integrated system identification and system optimization, IEEE Transactions on Systems, Man and Cybernaties, 1(3), 296-297. https://doi.org/10.1109/TSMC.1971.4308298
  9. Herroelen, W., Reyck, B. D., and Demeulemeester, E. (1998) Resource-constrained project scheduling: A survey of recent developments, Computers and Operations Research, 25(4), 279-302. https://doi.org/10.1016/S0305-0548(97)00055-5
  10. Hsu, C. C. and Kim, D. S. (2005) A new heuristic for the multi-mode resource investment problem, Journal of the Operational Research Society, 56(4),406-413. https://doi.org/10.1057/palgrave.jors.2601827
  11. Kolisch, R. and Drexl, A. (1997) Local search for nonpreemptive multi-mode resource-constrained project scheduling, IIE Transactions, 29(11), 987-999.
  12. Kolisch, R. and Hartmann, S. (2006) Experimental investigation of heuristics for resource-constrained project scheduling: An update, European Journal of Operational Research, 174(1), 23-37. https://doi.org/10.1016/j.ejor.2005.01.065
  13. Kolisch, R. and Sprecher, A. (1997) PSPLIB–A project scheduling problem library, European journal of Operational Research, 96(1), 205-216. https://doi.org/10.1016/S0377-2217(96)00170-1
  14. Kolisch, R., Sprecher, A., and Drexl, A. (1995) Characterization and generation of a general class of resource- constrained project scheduling problems, Management Science, 41(10), 1693-1703. https://doi.org/10.1287/mnsc.41.10.1693
  15. Li, K.Y. and Willis, R. J. (1992) An iterative scheduling technique for resource-constrained project scheduling, European Journal of Operational Research, 56(3), 370-379. https://doi.org/10.1016/0377-2217(92)90320-9
  16. Ljubic, I. and Raidl, G. R. (2003) A memetic algorithm for minimum-cost vertex-biconnectivity augmentation of graphs, Journal of Heuristics, 9(5), 401-427. https://doi.org/10.1023/B:HEUR.0000004810.27436.30
  17. Moscato, P. (1989) On evolutions, search, optimization, genetic algorithms and martial arts: toward memetic algorithms, Technical Report, Caltech Concurrent Computer Program Report, California Institute Technology, Pasadena, CA.
  18. Moscato, P. (1999) Memetic algorithms: a short introduction, In D. Corne, F. Glover and M. Dorigo, eds. New Ideas in Optimization, McGraw-Hill, 219-234.
  19. Patterson, J. H. (1984) A comparison of exact procedures for solving the multiple constrained resource project scheduling problem, Management Science, 30(7), 854-867. https://doi.org/10.1287/mnsc.30.7.854
  20. Prabuddha, D. E., Dunne, E. J., and Ghosh, J. B. (1997) Complexity of the discrete time-cost tradeoff problem for project networks, Operations research, 45(2), 302-306. https://doi.org/10.1287/opre.45.2.302
  21. Sprecher, A. (1994) Resource-constrained project sche-duling -exact methods for the multi-mode case, Lecture Notes in Economics and Mathematics, No 409, Springer, Berlin, Germany.
  22. Talbot, F. B. (1982) Resource constrained project scheduling with time-resource tradeoffs: the nonpreemptive case, Management Science, 28(10), 1197- 1210. https://doi.org/10.1287/mnsc.28.10.1197
  23. Tormos, P. and Lova, A. (2001) A competitive heuristic solution technique for resource-constrained project scheduling, Annals of Operations Research, 102(1- 4), 65-81. https://doi.org/10.1023/A:1010997814183
  24. Tormos, P. and Lova, A. (2003) An efficient multi-pass heuristic for project scheduling with constrained resources, International Journal of Production Research, 41(5), 1071-1086. https://doi.org/10.1080/0020754021000033904
  25. Valls, V., Ballestin, F., and Quintanilla, S. (2005) Justification and RCPSP: a technique that pays, European Journal of Operational Research, 165(2), 375-386. https://doi.org/10.1016/j.ejor.2004.04.008
  26. Vanhoucke, M., Demeulemeester, E., and Herroelen, W. (2002) Discrete time/cost trade-offs in project scheduling with time-switch constraints, Journal of the Operations Research Society, 53(7), 741-751. https://doi.org/10.1057/palgrave.jors.2601351
  27. Weglarz, J. (1999) Project Scheduling: Recent models, Algorithms and Applications, Norwell, MA: Kluwer.
  28. Wuliang, P. and Chengen, W. A. (2009) Multi-mode resource-constrained discrete time-cost tradeoff problem and its genetic algorithm based solution, International Journal of Project Management, 27 (6), 600-609. https://doi.org/10.1016/j.ijproman.2008.10.009
  29. Yamashita, D. S. Armentano, V. A., and Laguna, M. (2006) Scatter search for project scheduling with resource availability cost, European Journal of Operational Research, 169(2), 623-637. https://doi.org/10.1016/j.ejor.2004.08.019