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2019, vol. 47, iss. 4, pp. 775-781
A real-time optimization algorithm for the integrated planning and scheduling problem towards the context of Industry 4.0
University of Minho, Centro Algoritmi, Portugal + University of Minho, School of Engineering, Department of Production and Systems Engineering, Guimarães, Portugal

emailtelmo@dps.uminho.pt
Project:
This work has been supported by FCT - Fundação para a Ciência e a Tecnologia within the Project Scope: UID/CEC/00319/2019.

Abstract
In this paper, we analyze the integration of two different problems in the supply chain, concerning the tactical and operational levels, and how the integration of two complex problems can be profitable towards the context of industry 4.0. More precisely, we address the integrated planning and scheduling problem on parallel and identical machines, seeking fast solutions that are globally optimal and flexible. In the planning phase, a set of jobs is assigned to their processing periods of time. On the other hand, in the scheduling phase, jobs are assigned to a machine in a given order. We propose a new metaheuristic approach through a variable neighborhood descent algorithm which iteratively explores four neighborhood structures with a first improvement strategy. The suggested algorithm was extensively tested using a large set of benchmark instances. The obtained results are discussed and compared with other approaches from literature.
References
Abdel-Basset, M., Manogaran, G., Mohamed, M. (2018) Internet of Things (IoT) and its impact on supply chain: A framework for building smart, secure and efficient systems. Future Generation Computer Systems, 86: 614-628
Chang, Y.C., Lee, C.Y. (2004) Machine scheduling with job delivery coordination. European Journal of Operational Research, 158(2): 470-487
Chen, B., Wan, J., Shu, L., Li, P., Mukherjee, M., Yin, B. (2018) Smart factory of Industry 4.0: Key technologies, application case, and challenges. IEEE Access, 6: 6505-6519
Cheng, Y., Chen, K., Sun, H., Zhang, Y., Tao, F. (2018) Data and knowledge mining with big data towards smart production. Journal of Industrial Information Integration, 9: 1-13
Chu, Y., You, F. (2014) Integrated planning and scheduling by hybrid solution method. in: 53rd IEEE Conference on Decision and Control, IEEE, pp. 6818-6823
Edtmayr, T., Sunk, A., Sihn, W. (2016) An approach to integrate parameters and indicators of sustainability management into value stream mapping. Procedia CIRP, 41: 289-294
Gerlitz, L. (2016) Design management as a domain of smart and sustainable enterprise: Business modelling for innovation and smart growth in Industry 4.0. Entrepreneurship and Sustainability Issues, 3(3): 244-268
Grangel-González, I., Baptista, P., Halilaj, L., Lohmann, S., Vidal, M.E., Mader, C., Auer, S. (2017) The industry 4.0 standards landscape from a semantic integration perspective. in: 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, pp. 1-8, September
Hansen, P., Mladenović, N. (2003) Variable neighborhood search. in: Handbook of metaheuristics, 24(11), 145-184
Hansen, P., Mladenović, N., Todosijević, R., Hanafi, S. (2017) Variable neighborhood search: Basics and variants. EURO Journal on Computational Optimization, 5(3): 423-454
Ivanov, D., Dolgui, A., Sokolov, B., Werner, F., Ivanova, M. (2016) A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0. International Journal of Production Research, 54(2): 386-402
Kis, T., Kovács, A. (2012) A cutting plane approach for integrated planning and scheduling. Computers & Operations Research, 39(2): 320-327
Kleindorfer, P.R., Singhal, K., van Wassenhove, L.N. (2005) Sustainable operations management. Production and Operations Management, 14(4): 482-492
Leite, M., Pinto, T., Alves, C. (2017) A local search heuristic for integrated process planning and scheduling. in: Eighth International Conference on Business Sustainability 2018, Póvoa do Varzim, Portugal, submitted
Leite, M., Alves, C., Pinto, T. (2017) Variable neighborhood search for integrated planning and scheduling. in: Lecture Notes in Computer Science: Computational Science and Its Applications - ICCSA 2017, Cham: Springer International Publishing, 709-724, vol 10405
Pfeffer, J., Graube, M., Reipschlaeger, P., Arndt, S., Urbas, L., Dachselt, R., Stelzer, R. (2015) Towards collaborative plant control using a distributed information and interaction space. in: 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA), IEEE, pp. 1-4
Rajković, M., Zrnić, N., Kosanić, N., Borovinšek, M., Lerher, T. (2017) A multi-objective optimization model for minimizing cost, travel time and Co2 emission in an AS/RS. FME Transactions, vol. 45, br. 4, str. 620-629
Rietz, J., Alves, C., Braga, N., Valério, D.C.J. (2016) An exact approach based on a new pseudo-polynomial network flow model for integrated planning and scheduling. Computers & Operations Research, 76: 183-194
Shafiq, S.I., Sanin, C., Szczerbicki, E., Toro, C. (2015) Virtual engineering object / virtual engineering process: A specialized form of Cyber Physical System for Industrie 4.0. Procedia Computer Science, 60: 1146-1155
Stank, T., Autry, C., Daugherty, P., Closs, D. (2015) Reimagining the 10 megatrends that will revolutionize supply chain logistics. Transportation Journal, 54(1): 7-32
Trappey, A.J.C., Trappey, C.V., Fan, C., Hsu, A.P.T., Li, X., Lee, I.J.Y. (2017) IoT patent roadmap for smart logistic service provision in the context of Industry 4.0. Journal of the Chinese Institute of Engineers, 40(7): 593-602
Trstenjak, M., Cosic, P. (2017) Process planning in Industry 4.0 environment. Procedia Manufacturing, 11: 1744-1750
Tuček, D., Tučková, Z., Jelínková, D. (2017) Merenje performansi energetskih procesa u češkim kompanijama. FME Transactions, vol. 45, br. 4, str. 670-677
Ungurean, I., Gaitan, N.C., Gaitan, V.G. (2014) An IoT architecture for things from industrial environment. in: 2014 10th International Conference on Communications (COMM), IEEE, pp. 1-4, May
Wan, J., Cai, H., Zhou, K. (2015) Industrie 4.0: Enabling technologies. in: Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things, IEEE, pp 135-140
Xu, L.D., Xu, E.L., Li, L. (2018) Industry 4.0: State of the art and future trends. International Journal of Production Research, 56(8): 2941-2962
Yüksek, L., Kaleli, H., Özener, O., Özoğuz, B. (2009) The effect and comparison of biodiesel-diesel fuel on crankcase oil, diesel engine performance and emissions. FME Transactions, vol. 37, br. 2, str. 91-97
 

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article language: English
document type: unclassified
DOI: 10.5937/fmet1904775L
published in SCIndeks: 10/10/2019
Creative Commons License 4.0

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