Abstract
Among all types of production environment, identical parallel machines are frequently used to increase the manufacturing capacity of the drilling operation in Taiwan printed circuit board (PCB) industries. So when a manager plans the production scheduling, multiple but conflicting objectives are often considered. Unlike the single objective problem, the multiple-objective version no longer looks for an individual optimal solution, but a Pareto front consisting of a set of non-dominated solutions. The manager then can select one of the alternatives from the set. For this matter, our research aims at applying a variable neighborhood search (VNS) algorithm in the identical parallel machine scheduling problem (IPMSP) with two conflicting objectives: makespan and total tardiness. In VNS, two neighborhoods are defined – insert a job to a different position or swap two jobs in the sequence. To save the computational expense, one of the neighborhoods is randomly selected for the target solution which is also arbitrarily chosen from the current Pareto front. The proposed VNS algorithm is tested on a set of real data collected from a leading PCB factory in Taiwan and its performance is compared with well-known methods in the literature. The computational results show that VNS outperforms all competing algorithms – SPGA, MOGA, NSGA-II, SPEA-II, and MACO in terms of solution quality and computational time.
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References
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman, New York (1979)
Chang, P.C., Chen, S.H., Lin, K.L.: Two-phase Sub-population Genetic Algorithm for Parallel Machine Scheduling Problem. Expert Syst. Appl. 29(3), 705–712 (2005)
Liang, Y.C., Hsiao, Y.M.: A Multiple Ant Colony Optimization Algorithm for a Bi-objective Parallel Machine Scheduling Problem in Taiwan PCB Industries. In: The 3rd Annual Conference of the Operations Research Society of Taiwan, ORSTW074 (2006)
Hansen, P., Mladenović, N., Pérez, J.A.M.: Variable Neighborhood Search: Methods and Applications. Ann. Oper. Res. 175, 367–407 (2010)
Liang, Y.C., Chen, Y.C.: Redundancy Allocation of Series-parallel Systems Using a Variable Neighborhood Search Algorithm. Reliab. Eng. Syst. Saf. 92, 323–331 (2007)
Geiger, M.J.: Randomised Variable Neighbourhood Search for Multi Objective Optimisation. In: Proceedings of EU/ME Workshop: Design and Evaluation of Advanced Hybrid Meta-Heuristics, pp. 34–42 (2004)
Liang, Y.C., Lo, M.H.: Multi-objective Redundancy Allocation Optimization Using a Variable Neighborhood Search Algorithm. J. Heuristics 16(3), 511–535 (2010)
Ishibuchi, H., Yoshida, T., Murata, T.: Balance between Genetic Search and Local Search in Memetic Algorithms for Multiobjective Permutation Flowshop Scheduling. IEEE Trans. Evol. Comput. 7(2), 204–223 (2003)
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© 2011 Springer-Verlag Berlin Heidelberg
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Liang, YC., Tien, CY. (2011). Variable Neighborhood Search for Drilling Operation Scheduling in PCB Industries. In: Huang, DS., Gan, Y., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing. ICIC 2011. Lecture Notes in Computer Science, vol 6838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24728-6_8
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DOI: https://doi.org/10.1007/978-3-642-24728-6_8
Publisher Name: Springer, Berlin, Heidelberg
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