Abstract
The scheduling problems are very common in any industry or organization. The software project management is frequently faced with different scheduling problems. We present the Resource-Constrained Project Scheduling problem as a generic problem in which different resources must be assigned to different activities, so that the make span is minimized and a set of precedence constraints between activities and resource allocation to these activities are met. This Problem is a NP-hard combinatorial optimization problem. In this paper we present the model the resolution of the problem through the Artificial Bee Colony algorithm. The Artificial Bee Colony is a metaheuristic that uses foraging behavior of honey bees for solving problems, especially applied to combinatorial optimization. We present an Artificial Bee Colony algorithm able to solve the Resource-Constrained Project Scheduling efficiently.
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References
Bouleimen, K., Lecocq, H.: A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. European Journal of Operational Research 149(2), 268–281 (2003)
Chen, R.-M., Wu, C.-L., Wang, C.-M., Lo, S.-T.: Using novel particle swarm optimization scheme to solve resource-constrained scheduling problem in psplib. Expert systems with applications 37(3), 1899–1910 (2010)
Chiarandini, M., Di Gaspero, L., Gualandi, S., Schaerf, A.: The balanced academic curriculum problem revisited. Journal of Heuristics 18(1), 119–148 (2012)
Dorndorf, U., Pesch, E., Phan-Huy, T.: A time-oriented branch-and-bound algorithm for resource-constrained project scheduling with generalised precedence constraints. Management Science 46(10), 1365–1384 (2000)
Hartmann, S.: A competitive genetic algorithm for resource-constrained project scheduling. Naval Research Logistics (NRL) 45(7), 733–750 (1998)
Herbots, J., Herroelen, W., Leus, R.: Experimental investigation of the applicability of ant colony optimization algorithms for project scheduling. DTEW Research Report 0459, 1–25 (2004)
Karaboga, D.: An idea based on honey bee swarm for numerical optimization. Technical report, Technical report-tr06, Erciyes university, engineering faculty, computer engineering department (2005)
Kempf, K., Uzsoy, R., Smith, S., Gary, K.: Evaluation and comparison of production schedules. Computers in industry 42(2), 203–220 (2000)
Mingozzi, A., Maniezzo, V., Ricciardelli, S., Bianco, L.: An exact algorithm for the resource-constrained project scheduling problem based on a new mathematical formulation. Management Science 44(5), 714–729 (1998)
Nonobe, K., Ibaraki, T.: Formulation and tabu search algorithm for the resource constrained project scheduling problem. In: Essays and Surveys in Metaheuristics, pp. 557–588. Springer (2002)
Pritsker, A.A.B., Waiters, L.J., Wolfe, P.M.: Multiproject scheduling with limited resources: A zero-one programming approach. Management science 16(1), 93–108 (1969)
Schirmer, A.: Case-based reasoning and improved adaptive search for project scheduling. Naval Research Logistics (NRL) 47(3), 201–222 (2000)
Valls, V., Ballestin, F., Quintanilla, S.: Justification and rcpsp: A technique that pays. European Journal of Operational Research 165(2), 375–386 (2005)
Zhang, H., Li, H., Tam, C.: Particle swarm optimization for resource-constrained project scheduling. International Journal of Project Management 24(1), 83–92 (2006)
Zhang, H., Li, X., Li, H., Huang, F.: Particle swarm optimization-based schemes for resource-constrained project scheduling. Automation in Construction 14(3), 393–404 (2005)
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Crawford, B., Soto, R., Johnson, F., Vargas, M., Misra, S., Paredes, F. (2015). A Scheduling Problem for Software Project Solved with ABC Metaheuristic. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9158. Springer, Cham. https://doi.org/10.1007/978-3-319-21410-8_48
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DOI: https://doi.org/10.1007/978-3-319-21410-8_48
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