Abstract
This paper describes the Software Project Scheduling Problem (SPSP) as a combinatorial optimization problem. In this problem raises the need for a process to assign a set of resources to tasks for a project in a given time, trying to decrease the duration and cost. The workers are the main resource in the project. We present the design of the resolution model to solve the SPSP using an algorithm of fireflies (Firefly Algorithm, FA). We illustrate the experimental results in order to demonstrate the viability and soundness of our approach.
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References
Alba, E., Chicano, F.: Software project management with gas. Inf. Sci. 177(11), 2380–2401 (2007)
Barreto, A., de Barros, M.O., Werner, C.M.L.: Staffing a software project: a constraint satisfaction and optimization-based approach. Comput. Oper. Res. 35(10), 3073–3089 (2008)
Chandrasekaran, K., Simon, S.P., Padhy, N.P.: Binary real coded firefly algorithm for solving unit commitment problem. Inf. Sci. 249, 67–84 (2013)
Chang, C.K., Jiang, H.Y., Di, Y., Zhu, D., Ge, Y.: Time-line based model for software project scheduling with genetic algorithms. Inf. Softw. Technol. 50(11), 1142–1154 (2008)
Crawford, B., Soto, R., Castro, C., Monfroy, E.: Extensible cp-based autonomous search. In: Proceedings of HCI International. CCIS, vol. 173, pp. 561–565. Springer (2011)
Crawford, B., Soto, R., Monfroy, E., Palma, W., Castro, C., Paredes, F.: Parameter tuning of a choice-function based hyperheuristic using particle swarm optimization. Expert Syst. Appl. 40(5), 1690–1695 (2013)
Monfroy, E., Castro, C., Crawford, B., Soto, R., Paredes, F., Figueroa, C.: A reactive and hybrid constraint solver. J. Exp. Theor. Artificial Intell. 25(1), 1–22 (2013)
Ozdamar, U.: A survey on the resource-constrained project scheduling problem. IIE Trans. 27(5), 574–586 (1995)
Xiao, J., Ao, X.T., Tang, Y.: Solving software project scheduling problems with ant colony optimization. Comput. Oper. Res. 40(1), 33–46 (2013)
Yang, X., He, X.: Firefly algorithm: recent advances and applications. arXiv:1308.3898
Yang, X.-S.: Firefly algorithms for multimodal optimization. In: Watanabe, O., Zeugmann, T. (eds.) Stochastic Algorithms: Foundations and Applications. Lecture Notes in Computer Science, vol. 5792, pp. 169–178. Springer, Berlin (2009)
Yang, X.-S.: Nature-Inspired Optimization Algorithms, 1st edn. Elsevier Science Publishers B. V, Amsterdam, The Netherlands (2014)
Acknowledgments
Broderick Crawford is supported by Grant CONICYT/FONDECYT/REGULAR/1140897, Ricardo Soto is supported by Grant CONICYT/FONDECYT/INICIACION/11130459, Fernando Paredes is supported by Grant CONICYT/FONDECYT/REGULAR/1130455, Franklin Johnson is supported by Postgraduate Grant PUCV 2015.
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Crawford, B., Soto, R., Johnson, F., Valencia, C., Paredes, F. (2016). Firefly Algorithm to Solve a Project Scheduling Problem. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Silhavy, P., Prokopova, Z. (eds) Artificial Intelligence Perspectives in Intelligent Systems. Advances in Intelligent Systems and Computing, vol 464. Springer, Cham. https://doi.org/10.1007/978-3-319-33625-1_40
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DOI: https://doi.org/10.1007/978-3-319-33625-1_40
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