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The Basic Multi-Project Scheduling Problem

  • José Fernando Gonçalves
  • Jorge José de Magalhães Mendes
  • Mauricio G. C. Resende
Chapter
Part of the International Handbooks on Information Systems book series (INFOSYS)

Abstract

In this chapter the Basic Multi-Project Scheduling Problem (BMPSP) is described, an overview of the literature on multi-project scheduling is provided, and a solution approach based on a biased random-key genetic algorithm (BRKGA) is presented. The BMPSP consists in finding a schedule for all the activities belonging to all the projects taking into account the precedence constraints and the availability of resources, while minimizing some measure of performance. The representation of the problem is based on random keys. The BRKGA generates priorities, delay times, and release dates, which are used by a heuristic decoder procedure to construct parameterized active schedules. The performance of the proposed approach is validated on a set of randomly generated problems.

Keywords

Genetic algorithm Meta-heuristics Multi-project scheduling Random keys 

Notes

Acknowledgements

This work has been partially supported by funds granted by the ERDF through the Programme COMPETE and by the Portuguese Government through FCT, the Foundation for Science and Technology, project PTDC/EGE-GES/117692/2010.

References

  1. Ash R (1999) Activity scheduling in the dynamic, multi-project setting: choosing heuristics through deterministic simulation. In: Proceedings of the 1999 winter simulation conference, Phoenix, pp 937–941Google Scholar
  2. Baker KR (1974) Introduction to sequencing and scheduling. Wiley, New YorkGoogle Scholar
  3. Bean JC (1994) Genetics and random keys for sequencing and optimization. ORSA J Comput 6:154–160CrossRefGoogle Scholar
  4. Błażewicz J, Lenstra JK, Rinnooy Kan AHG (1983) Scheduling subject to resource constraints: classification and complexity. Discrete Appl Math 5:11–24CrossRefGoogle Scholar
  5. Bock D, Patterson J (1990) A comparison of due date setting, resource assignment, and job preemption heuristics for the multi-project scheduling problem. Decis Sci 21:387–402CrossRefGoogle Scholar
  6. Browning TR, Yassine AA (2010) Resource-constrained multi-project scheduling: priority rule performance revisited. Int J Prod Econ 126(2):212–228CrossRefGoogle Scholar
  7. Cai Z, Li X (2012) A hybrid genetic algorithm for resource-constrained multi-project scheduling problem with resource transfer time. In: Proceedings of the 2012 IEEE international conference on automation science and engineering (CASE 2012), Seoul, pp 569–574Google Scholar
  8. Deckro R, Winkofsky E, Hebert J, Gagnon R (1991) A decomposition approach to multi-project scheduling. Eur J Oper Res 51:110–118CrossRefGoogle Scholar
  9. Drexl A (1991) Scheduling of project networks by job assignment. Manag Sci 37(12):1590–1602CrossRefGoogle Scholar
  10. Dumond J, Mabert V (1988) Evaluating project scheduling and due date assignment procedures: an experimental analysis. Manag Sci 34(1):101–118CrossRefGoogle Scholar
  11. Fendley L (1968) Towards the development of a complete multiproject scheduling system. J Ind Eng 19(10):505–515Google Scholar
  12. Gonçalves JF, Almeida JR (2002) A hybrid genetic algorithm for assembly line balancing. J Heuristics 8:629–642CrossRefGoogle Scholar
  13. Gonçalves JF, Beirão NC (1999) Um algoritmo genético baseado em chaves aleatórias para sequenciamento de operações. Revista da Associação Portuguesa de Investigação Operacional 19:123–137 (in Portuguese)Google Scholar
  14. Gonçalves JF, Resende MGC (2004) An evolutionary algorithm for manufacturing cell formation. Comput Ind Eng 47:247–273CrossRefGoogle Scholar
  15. Gonçalves JF, Resende MGC (2011a) Biased random-key genetic algorithms for combinatorial optimization. J Heuristics 17:487–525CrossRefGoogle Scholar
  16. Gonçalves JF, Resende MGC (2011b) A parallel multi-population genetic algorithm for a constrained two-dimensional orthogonal packing problem. J Comb Optim 22:180–201CrossRefGoogle Scholar
  17. Gonçalves JF, Resende MGC (2012) A parallel multi-population biased random-key genetic algorithm for a container loading problem. Comput Oper Res 39:179–190CrossRefGoogle Scholar
  18. Gonçalves JF, Resende MG (2013) A biased random key genetic algorithm for 2D and 3D bin packing problems. Int J Prod Econ 145(2):500–510CrossRefGoogle Scholar
  19. Gonçalves JF, Resende MG (2014) An extended akers graphical method with a biased random-key genetic algorithm for job-shop scheduling. Int Trans Oper Res 21(2):215–246CrossRefGoogle Scholar
  20. Gonçalves JF, Sousa PSA (2011) A genetic algorithm for lot sizing and scheduling under capacity constraints and allowing backorders. Int J Prod Res 49:2683–2703CrossRefGoogle Scholar
  21. Gonçalves JF, Mendes JJM, Resende MGC (2005) A hybrid genetic algorithm for the job shop scheduling problem. Eur J Oper Res 167:77–95CrossRefGoogle Scholar
  22. Gonçalves JF, Mendes JJM, Resende MGC (2008) A genetic algorithm for the resource constrained multi-project scheduling problem. Eur J Oper Res 189:1171–1190CrossRefGoogle Scholar
  23. Krüger D, Scholl A (2010) Managing and modelling general resource transfers in (multi-) project scheduling. OR Spectr 32(2):369–394CrossRefGoogle Scholar
  24. Kumanam S, Raja K (2011) Multi-project scheduling using a heuristic and memetic alogrithm. J Manuf Sci Prod 10(3–4):249–256Google Scholar
  25. Kurtulus I (1985) Multiproject scheduling: analysis of scheduling strategies under unequal delay penalties. J Oper Manag 5(3):291–307CrossRefGoogle Scholar
  26. Kurtulus I, Davis E (1982) Multi-project scheduling: categorization of heuristic rules performance. Manag Sci 28:161–172CrossRefGoogle Scholar
  27. Kurtulus I, Narula S (1985) Multi-project scheduling: analysis of project performance. IIE Trans 17:58–66CrossRefGoogle Scholar
  28. Lawrence S, Morton T (1993) Resource-constrained multi-project scheduling with tardy costs: comparing myopic bottleneck and resource pricing heuristics. Eur J Oper Res 64:168–187CrossRefGoogle Scholar
  29. Lova A, Tormos P (2001) Analysis of scheduling schemes and heuristic rules performance in resource-constrained multiproject scheduling. Ann Oper Res 102(1):263–286CrossRefGoogle Scholar
  30. Lova A, Tormos P (2002) Combining random sampling and backward-forward heuristics for resource-constrained multi-project scheduling. In: Proceedings of the eight international workshop on project management and scheduling, Valencia, pp 244–248Google Scholar
  31. Lova A, Maroto C, Tormos P (2000) A multicriteria heuristic method to improve resource allocation in multiproject scheduling. Eur J Oper Res 127:408–424CrossRefGoogle Scholar
  32. Mendes J (2003) Sistema de apoio à decisão para planeamento de sistemas de produção do tipo projecto. Ph.D. dissertation, Universidade do Porto, Porto (in Portuguese)Google Scholar
  33. Mohanthy R, Siddiq M (1989) Multiple projects multiple resources-constrained scheduling: some studies. Int J Prod Res 27(2):261–280CrossRefGoogle Scholar
  34. Özdamar L, Ulusoy G, Bayyigit M (1998) A heuristic treatment of tardiness and net present value criteria in resource constrained project scheduling. Int J Phys Distrib Logist Manag 28:805–824CrossRefGoogle Scholar
  35. Pritsker A, Allan B, Watters L, Wolfe P (1969) Multiproject scheduling with limited resources: a zero-one programming approach. Manag Sci 16:93–108CrossRefGoogle Scholar
  36. Shankar V, Nagi R (1996) A flexible optimization approach to multi-resource, multi-project planning and scheduling. In: Proceedings of 5th industrial engineering research conference, Minneapolis, pp 263–267Google Scholar
  37. Spears WM, Dejong KA (1991) On the virtues of parameterized uniform crossover. In: Proceedings of the fourth international conference on genetic algorithms, San Diego, pp 230–236Google Scholar
  38. Talbot FB (1982) Resource-constrained project scheduling with time-resource tradeoffs: the nonpreemptive case. Manag Sci 28(10):1197–1210CrossRefGoogle Scholar
  39. Tsubakitani S, Deckro R (1990) A heuristic for multi-project scheduling with limited resources in the housing industry. Eur J Oper Res 49:80–91CrossRefGoogle Scholar
  40. Vercellis C (1994) Constrained multi-project planning problems: a Lagrangean decomposition approach. Eur J Oper Res 78:267–275CrossRefGoogle Scholar
  41. Woodworth BM, Willie CJ (1975) A heuristic algorithm for resource leveling in multi-project, multi-resource scheduling. Decis Sci 6(3):525–540CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • José Fernando Gonçalves
    • 1
  • Jorge José de Magalhães Mendes
    • 2
  • Mauricio G. C. Resende
    • 3
  1. 1.LIAAD, INESC TECFaculdade de Economia da Universidade do PortoPortoPortugal
  2. 2.Depto. de Engenharia CivilInstituto Superior de Engenharia do PortoPortoPortugal
  3. 3.Algorithms and Optimization Research DepartmentAT&T Labs ResearchFlorham ParkUSA

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