Abstract
This paper deals with the problem of scheduling of mobile robots taking into account preemption cases in a flexible manufacturing system (FMS). In addition to capability of transporting materials between some machines, mobile robots are able to perform manufacturing tasks at other machines by using their manipulation arms. These manufacturing tasks can be preempted to allow mobile robots to transport materials when needed. The performance criterion is to minimize time required to complete all tasks, i.e. makespan. A mixed-integer programming (MIP) model is formulated to find the optimal solutions for the problem. Numerical experiments are investigated to demonstrate results of the proposed approach.
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References
Abdelmaguid, T.F., Nassef, A.O., Kamal, B.A., Hassan, M.F.: A Hybrid GA/Heuristic Approach to the Simultaneous Scheduling of Machines and Automated Guided Vehicles. Int. J. Prod. Res. 42, 267–281 (2004)
Bilge, Ü., Ulusoy, G.: A Time Window Approach to Simultaneous Scheduling of Machines and Material Handling System in an FMS. Oper. Res. 43, 1058–1070 (1995)
Blazewicz, J., Eiselt, H.A., Finke, G., Laporte, G., Weglartz, J.: Scheduling Tasks and Vehicles in a Flexible Manufacturing System. Int. J. Flex. Manuf. Syst. 4, 5–16 (1991)
Bocewicz, G.: Robustness of Multimodal Transportation Networks. Eksploatacja i Niezawodnosc – Maintenance and Reliability 16, 259–269 (2014)
Bocewicz, G., Banaszak, Z.: Declarative Approach to Cyclic Steady States Space Refinement: Periodic Processes Scheduling. Int. J. Adv. Manuf. Tech. 67, 137–155 (2013)
Caumond, A., Lacomme, P., Moukrim, A., Tchernev, N.: A MILP for Scheduling Problems in an FMS with One Vehicle. Eur. J. Oper. Res. 199, 706–722 (2009)
Dang, Q.-V., Nielsen, I.E., Bocewicz, G.: A Genetic Algorithm-based Heuristic for Part-Feeding Mobile Robot Scheduling Problem. In: Rodríguez, J.M.C., Pérez, J.B., Golinska, P., Giroux, S., Corchuelo, R. (eds.) Trends in PAAMS. AISC, vol. 157, pp. 85–92. Springer, Heidelberg (2012)
Dang, Q.V., Nielsen, I., Steger-Jensen, K.: Scheduling a Single Mobile Robot Incorporated into Production Environment. In: Golinska, P. (ed.) EcoProduction and Logistics. EcoProduction, pp. 185–201. Springer, Heidelberg (2013)
Deroussi, L., Gourgand, M., Tchernev, N.: A Simple Metaheuristic Approach to the Simultaneous Scheduling of Machines and Automated Guided Vehicles. Int. J. Prod. Res. 46, 2143–2164 (2008)
Hvilshøj, M., Bøgh, S., Nielsen, O.S., Madsen, O.: Multiple Part Feeding – Real-world Application for Mobile Manipulators. Assemb. Autom. 32, 62–71 (2012)
Lacomme, P., Larabi, M., Tchernev, N.: Job-shop Based Framework for Simultaneous Scheduling of Machines and Automated Guided Vehicles. Int. J. Prod. Econ., 24–34 (2013)
Lin, L., Shinn, S.W., Gen, M., Hwang, H.: Network Model and Effective Evolutionary Approach for AGV Dispatching in Manufacturing System. J. Intell. Manuf. 17, 465–477 (2006)
Sitek, P., Wikarek, J.: A Hybrid Method for Modeling and Solving Constrained Search Problems. In: Federated Conference on Computer Science and Information Systems (FedCSIS), pp. 385–392. IEEE Press, Kraków (2013)
Soylu, M., Özdemirel, N.E., Kayaligil, S.: A Self-organizing Neural Network Approach for the Single AGV Routing Problem. Eur. J. Oper. Res. 121, 124–137 (2000)
Ulusoy, G., Sivrikaya-Şerifoǧlu, F., Bilge, Ü.: A Genetic Algorithm Approach to the Simultaneous Scheduling of Machines and Automated Guided Vehicles. Comput. Oper. Res. 24, 335–351 (1997)
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Nielsen, I., Dang, QV., Nielsen, P., Pawlewski, P. (2014). Scheduling of Mobile Robots with Preemptive Tasks. In: Omatu, S., Bersini, H., Corchado, J., Rodríguez, S., Pawlewski, P., Bucciarelli, E. (eds) Distributed Computing and Artificial Intelligence, 11th International Conference. Advances in Intelligent Systems and Computing, vol 290. Springer, Cham. https://doi.org/10.1007/978-3-319-07593-8_3
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DOI: https://doi.org/10.1007/978-3-319-07593-8_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07592-1
Online ISBN: 978-3-319-07593-8
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