Self-configuring Intelligent Water Drops Algorithm for Software Project Scheduling Problem
At present a large number exists of metaheuristics that can support some process in the industry; however, there is a great difficulty to be overcome before use, that is the adjustment of the parameters that they use. It is already known the significant impact that they have on their behavior the correct choice of their values. Given the importance that has the proper adjustment of the parameters, our work presents a self-adjusting alternative for a constructive metaheuristic called Intelligent Water Drops. To evaluate our proposal we solve the Software Project Scheduling Problem, obtaining very similar results and one case superior to the version with manual adjustment.
KeywordsIntelligent water drops Project management Software Project Scheduling Problem
Broderick Crawford is supported by grant CONICYT/FONDECYT/REGULAR 1171243 and Ricardo Soto is supported by Grant CONICYT/FONDECYT/REGULAR/1160455, Gino Astorga is supported by Postgraduate Grant, Pontificia Universidad Catolica de Valparaíso, 2015 and José Lemus is supported by INF-PUCV 2018.
- 4.Crawford, B., Soto, R., Astorga, G., Castro, C., Paredes, F., Misra, S., Rubio, J.M.: Solving the software project scheduling problem using intelligent water drops. Tehnički vjesnik 25(2), 350–357 (2018)Google Scholar
- 5.Crawford, B., Soto, R., Castro, C., Monfroy, E.: Extensible CP-based autonomous search. In: International Conference on Human-Computer Interaction, pp. 561–565. Springer (2011)Google Scholar
- 6.Crawford, B., Soto, R., Johnson, F., Misra, S., Paredes, F., Olguín, E.: Software project scheduling using the hyper-cube ant colony optimization algorithm. Tech. Gaz. 22(5), 1171–1178 (2015)Google Scholar
- 9.Hamadi, Y., Monfroy, E., Saubion, F.: What is autonomous search? In: Hybrid Optimization, pp. 357–391. Springer (2011)Google Scholar
- 12.Prabha, D.R., Jayabarathi, T., Umamageswari, R., Saranya, S.: Optimal location and sizing of distributed generation unit using intelligent water drop algorithm. Sustain. Energy Technol. Assess. 11, 106–113 (2015)Google Scholar
- 15.Soto, R., Crawford, B., Monfroy, E., Bustos, V.: Using autonomous search for generating good enumeration strategy blends in constraint programming. In: International Conference on Computational Science and Its Applications, pp. 607–617. Springer (2012)Google Scholar