A multi-objective optimization model for minimizing investment expenses, cycle times and CO2 footprint of an automated storage and retrieval systems
Abstract
A new optimization model of Automated Storage and Retrieval Systems (AS/RS) containing three objective and four constraint functions is presented in this paper. Majority of the researchers and publications in material handling field had performed optimization of different decision variables, but with single objective function only. Most common functions are: minimum travel time, maximum throughput capacity, minimum cost, maximum energy efficiency, etc. To perform the simultaneous optimization of objective functions (minimum: “investment expenses”, “cycle times”, “CO2 footprint”) the Non-dominated Sorting Genetic Algorithm II (NSGA II) was used. The NSGA II is a tool for finding the Pareto optimal solutions on the Pareto line. Determining the performance of the system is the main goal of our model. Since AS/RS are not flexible in terms of layout and organizational changes once the system is up and running, the proposed model could be a very helpful tool for the warehouse planners in the early stages of warehouse design.
Keyword : warehouses, automated storage and retrieval system, multi-objective optimization, performance analysis, mathematical modelling
How to Cite
Rajković, M., Zrnić, N., Kosanić, N., Borovinšek, M., & Lerher, T. (2019). A multi-objective optimization model for minimizing investment expenses, cycle times and CO2 footprint of an automated storage and retrieval systems. Transport, 34(2), 275-286. https://doi.org/10.3846/transport.2019.9686
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Tappia, E.; Marchet, G.; Melacini, M.; Perotti, S. 2015. Incorporating the environmental dimension in the assessment of automated warehouses, Production Planning & Control: the Management of Operations 26(10): 824–838. https://doi.org/10.1080/09537287.2014.990945
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Vidovics, H. 1994. Die Systemanalyse und Umschlagleistungen von Regalförderzeugen mit Mehrfachlastaufnahmemitteln. Dissertation. Technische Universität Graz, Österreich. 213 S. (in German).
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Zrnić, Đ.; Savić, D. 1990. Simulacija procesa unutrašnjeg transporta. Univerzitet u Beogradu, Srbija. 251 p. (in Serbian).
Ashayeri, J.; Gelders, L.; Van Wassenhove, L. 1985. A microcomputer-based optimization model for the design of automated warehouses, International Journal of Production Research 23(4): 825–839. https://doi.org/10.1080/00207548508904750
Bafna, K. M.; Reed, R. 1972. An analytical approach to design of high-rise stacker crane warehouse systems, Journal of Industrial Engineering 4(10): 8–14.
Bekker, J. 2013. Multi-objective buffer space allocation with the cross-entropy method, International Journal of Simulation Modelling 12(1): 50–61. https://doi.org/10.2507/IJSIMM12(1)5.228
Borovinšek, M.; Ekren, B. Y.; Burinskienė, A.; Lerher, T. 2017. Multi-objective optimisation model of shuttle-based storage and retrieval system, Transport 32(2): 120–137. https://doi.org/10.3846/16484142.2016.1186732
Bortolini, M.; Accorsi, R.; Gamberi, M.; Manzini, R.; Regattieri, A. 2015a. Optimal design of AS/RS storage systems with three-class-based assignment strategy under single and dual command operations, The International Journal of Advanced Manufacturing Technology 79(9–12): 1747–1759. https://doi.org/10.1007/s00170-015-6872-1
Bortolini, M.; Faccio, M.; Gamberi, M.; Manzini, R. 2015b. Diagonal cross-aisles in unit load warehouses to increase handling performance, International Journal of Production Economics 170: 838–849. https://doi.org/10.1016/j.ijpe.2015.07.009
Bortolini, M.; Faccio, M.; Ferrari, E.; Gamberi, M.; Pilati, F. 2017. Time and energy optimal unit-load assignment for automatic S/R warehouses, International Journal of Production Economics 190: 133–145. https://doi.org/10.1016/j.ijpe.2016.07.024
Bozer, A. Y.; White, J. A. 1984. Travel-time models for automated storage/retrieval systems, IIE Transactions 16(4): 329–338. https://doi.org/10.1080/07408178408975252
Colicchia, C.; Creazza, A.; Dallari, F.; Melacini, M. 2016. Ecoefficient supply chain networks: development of a design framework and application to a real case study, Production Planning & Control: the Management of Operations 27(3): 157–168. https://doi.org/10.1080/09537287.2015.1090030
Diao, X.; Li, H.; Zeng, S.; Tam, V. W.; V.; Guo, H. 2011. A Pareto multi-objective optimization approach for solving time-cost-quality tradeoff problems, Technological and Economic Development of Economy 17(1): 22–41. https://doi.org/10.3846/13928619.2011.553988
Foster, D. 1970. Automatic Warehouse. Iliffe. 272 p.
Graves, S. C.; Hausman, W. H.; Schwarz, B. L. 1977. Storage-retrieval interleaving in automatic warehousing systems, Management Science 23(9): 935–945. https://doi.org/10.1287/mnsc.23.9.935
Gu, J.; Goetschalckx, M.; McGinnis, L. F. 2007. Research on warehouse operation: a comprehensive review, European Journal of Operational Research 177(1): 1–21. https://doi.org/10.1016/j.ejor.2006.02.025
Gudehus, T. 1973. Grundlagen der Kommissioniertechnik. Dynamik der Warenverteil- und Lagersysteme. Cornelsen Verlag GmbH. 214 S. (in German).
Hausman, W. H.; Schwarz, L. B.; Graves, S. C. 1976. Optimal storage assignment in automatic warehousing systems, Management Science 22(6): 629–638. https://doi.org/10.1287/mnsc.22.6.629
Hompel, M.; Schmidt, T. 2007. Warehouse Management: Automation and Organisation of Warehouse and Order Picking Systems. Springer. 357 p. https://doi.org/10.1007/978-3-540-35220-4
Hwang, H.; Lee, S. B. 1990. Travel-time models considering the operating characteristics of the storage and retrieval machine, International Journal of Production Research 28(10): 1779–1789. https://doi.org/10.1080/00207549008942833
Janilionis, V. V.; Bazaras, Ž.; Janilionis, V. 2016. Comparison of routing algorithms for storage and retrieval mechanism in cylindrical AS/RS, Transport 31(1): 11–21. https://doi.org/10.3846/16484142.2014.995130
Lerher, T. 2016. Travel time model for double-deep shuttle-based storage and retrieval system, International Journal of Production Research 54(9): 2519–2540. https://doi.org/10.1080/00207543.2015.1061717
Lerher, T. 2005. Model načrtovanja regalnih skladiščnih sistemov. Doktorska disertacija. Univerza v Mariboru, Slovenija. 192 s. (in Slovenian).
Lerher, T. 2013. Modern automation in warehousing by using the shuttle-based technology, in D. Arent, M. Freebush (Eds.). Automation Systems of the 21st Century: New Technologies, Applications and Impacts on the Environment & Industrial Processes, 51–86.
Lerher, T.; Borovinšek, M.; Šraml, M. 2013. A multi objective model for optimization of automated warehouses, in J. Cheung, H. Song (Eds.). Logistics: Perspectives, Approaches and Challenges, 87–110.
Lerher, T.; Edl, M.; Rosi, B. 2014. Energy efficiency model for the mini-load automated storage and retrieval systems, The International Journal of Advanced Manufacturing Technology 70(1–4): 97–115. https://doi.org/10.1007/s00170-013-5253-x
Lerher, T.; Ekren, B. Y.; Dukic, G.; Rosi, B. 2015a. Travel time model for shuttle-based storage and retrieval systems, The International Journal of Advanced Manufacturing Technology 78(9–12): 1705–1725. https://doi.org/10.1007/s00170-014-6726-2
Lerher, T.; Ekren, Y. B.; Sari, Z.; Rosi, B. 2015b. Simulation analysis of shuttle based storage and retrieval systems, International Journal of Simulation Modelling 14(1): 48–59. https://doi.org/10.2507/IJSIMM14(1)5.281
Lerher, T.; Potrč, I. 2006. The design and optimization of automated storage and retrieval systems, Strojniški vestnik – Journal of Mechanical Engineering 52(5): 268–291.
Marchet, G.; Melacini, M.; Perotti, S.; Tappia, E. 2013. Development of a framework for the design of autonomous vehicle storage and retrieval systems, International Journal of Production Research 51(14): 4365–4387. https://doi.org/10.1080/00207543.2013.778430
Ries, J. M.; Grosse, E. H.; Fichtinger, J. 2017. Environmental impact of warehousing: a scenario analysis for the United States, International Journal of Production Research 55(21): 6485–6499. https://doi.org/10.1080/00207543.2016.1211342
Roodbergen, K. J.; Vis, I. F. A. 2009. A survey of literature on automated storage and retrieval systems. European Journal of Operational Research 194(2): 343–362. https://doi.org/10.1016/j.ejor.2008.01.038
Rouwenhorst, B.; Reuter, B.; Stockrahm, V; Van Houtum, G. J.; Mantel, R. J.; Zijm, W. H. M. 2000. Warehouse design and control: framework and literature review, European Journal of Operational Research 122(3): 515–533. https://doi.org/10.1016/S0377-2217(99)00020-X
Smew, W.; Young, P.; Geraghty, J. 2013. Supply chain analysis using simulation, Gaussian process modelling and optimisation, International Journal of Simulation Modelling 12(3): 178–189. https://doi.org/10.2507/IJSIMM12(3)4.239
Tappia, E.; Marchet, G.; Melacini, M.; Perotti, S. 2015. Incorporating the environmental dimension in the assessment of automated warehouses, Production Planning & Control: the Management of Operations 26(10): 824–838. https://doi.org/10.1080/09537287.2014.990945
Tappia, E.; Roy, D.; De Koster, R.; Melacini, M. 2017. Modeling, analysis, and design insights for shuttle-based compact storage systems, Transportation Science 51(1): 269–295. https://doi.org/10.1287/trsc.2016.0699
UBA. 2016. Umweltbundesamt – UBA. Dessau-Roßlau, Deutschland. Available from Internet: http://www.umweltbundesamt.de (in German).
Vasili, M. R.; Tang, S. H.; Vasili, M. 2012. Automated storage and retrieval systems: a review on travel time models and control policies, in R. Manzini (Ed.). Warehousing in the Global Supply Chain, 159–209.
Vidovics, H. 1994. Die Systemanalyse und Umschlagleistungen von Regalförderzeugen mit Mehrfachlastaufnahmemitteln. Dissertation. Technische Universität Graz, Österreich. 213 S. (in German).
Vössner, S. 1994. Spielzeit Berechnung von Regalförderzeugen. Dissertation. Technische Universität Graz, Österreich. (in German).
Zrnić, Đ.; Savić, D. 1990. Simulacija procesa unutrašnjeg transporta. Univerzitet u Beogradu, Srbija. 251 p. (in Serbian).