Robust scheduling for Berth Allocation and Quay Crane Assignment Problem

[EN] Decision makers must face the dynamism and uncertainty of real-world environments when they need to solve the scheduling problems. Different incidences or breakdowns, for example, initial data could change or some resources could become unavailable, may eventually cause the infeasibility of the obtained schedule. To overcome this issue, a robust model and a proactive approach are presented for scheduling problems without any previous knowledge about incidences. This paper is based on proportionally distributing operational buffers among the tasks. In this paper, we consider the berth allocation problem and the quay crane assignment problem as a representative example of scheduling problems. The dynamism and uncertainty are managed by assessing the robustness of the schedules. The robustness is introduced by means of operational buffer times to absorb those unknown incidences or breakdowns. Therefore, this problem becomes a multiobjective combinatorial optimization problem that aims to minimize the total service time, to maximize the buffer times, and to minimize the standard deviation of the buffer times. To this end, a mathematical model and a new hybrid multiobjective metaheuristic is presented and compared with two well-known multiobjective genetic algorithms: NSGAII and SPEA2+.This work has been partially supported by by the Spanish Government under research project MINECO TIN2013-46511-C2-1-P, the project PIRSES-GA-2011-294931 (FP7-PEOPLE-2011-IRSES), and the predoctoral FPU fellowship (AP2010-4405).Rodríguez Molins, M.; Salido Gregorio, MA.; Barber Sanchís, F. (2014). Robust scheduling for Berth Allocation and Quay Crane Assignment Problem. Mathematical Problems in Engineering. 2014(1):1-17. https://doi.org/10.1155/2014/834927S11720141Imai, A., Chen, H. C., Nishimura, E., & Papadimitriou, S. (2008). The simultaneous berth and quay crane allocation problem. 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An Integrated Quay Crane Assignment and Scheduling Problem. Computers & Industrial Engineering, 73, 115-123. doi:10.1016/j.cie.2013.12.012Park, Y.-M., & Kim, K. H. (2003). A scheduling method for Berth and Quay cranes. OR Spectrum, 25(1), 1-23. doi:10.1007/s00291-002-0109-zZhang, C., Zheng, L., Zhang, Z., Shi, L., & Armstrong, A. J. (2010). The allocation of berths and quay cranes by using a sub-gradient optimization technique. Computers & Industrial Engineering, 58(1), 40-50. doi:10.1016/j.cie.2009.08.002Lambrechts, O., Demeulemeester, E., & Herroelen, W. (2007). Proactive and reactive strategies for resource-constrained project scheduling with uncertain resource availabilities. Journal of Scheduling, 11(2), 121-136. doi:10.1007/s10951-007-0021-0Hendriks, M., Laumanns, M., Lefeber, E., & Udding, J. T. (2010). Robust cyclic berth planning of container vessels. OR Spectrum, 32(3), 501-517. doi:10.1007/s00291-010-0198-zHan, X., Lu, Z., & Xi, L. (2010). 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This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field