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Intelligent Algorithms for Warehouse Management

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Intelligent Techniques in Engineering Management

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 87))

Abstract

Warehouses are important links in the supply chain; here, products are temporarily stored and retrieved subsequently from storage locations to fulfill customer’ orders. The order picking activity is one of the most time-consuming processes of a warehouse and is estimated to contribute for more than 55 % of the total cost of warehouse operations. Accordingly, scientists, as well as logistics managers, consider order picking as one of the most promising area for productivity improvements. This chapter is intended to provide the reader with an overview of different intelligent tools applicable to the issue of picking optimization. Specifically, by this chapter, we show how different types of intelligent algorithms can be used to optimize order picking operations in a warehouse, by decreasing the travel distance (and thus time) of pickers. The set of intelligent algorithms analyzed include: genetic algorithms, artificial neural networks, simulated annealing, ant colony optimization and particles swarm optimization models. For each intelligent algorithm, we start with a brief theoretical overview. Then, based on the available literature, we show how the algorithm can be implemented for the optimization of order picking operations. The expected pros and cons of each algorithm are also discussed.

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References

  • Aburto, L., Weber, R.: Improved supply chain management based on hybrid demand forecasts. Appl. Soft Comput. 7, 136–144 (2007)

    Article  Google Scholar 

  • Atmaca, E., Ozturk, A.: Defining order picking policy: a storage assignment model and a simulated annealing solution in AS/RS systems. Appl. Math. Model. 37(7), 5069–5079 (2013)

    Article  MathSciNet  Google Scholar 

  • Beasley, D., Bull, D.R., Martin, R.R.: An overview of genetic algorithms: parts 1 and 2. Univ. Comput. 15, 2–4 (1993)

    Google Scholar 

  • Bottani, E., Cecconi, M., Vignali, G., Montanari, R.: Optimisation of storage allocation in order picking operations through a genetic algorithm. Int. J. Logistics Res. Appl. 15(2), 127–146 (2012)

    Article  Google Scholar 

  • Bottani, E., Montanari, R., Volpi, A.: The impact of RFID and EPC network on the bullwhip effect in the Italian FMCG supply chain. Int. J. Prod. Econ. 124(2), 426–432 (2010)

    Article  Google Scholar 

  • Bottani, E., Rizzi, A.: Economical assessment of the impact of RFID technology and EPC system on the fast moving consumer goods supply chain. Int. J. Prod. Econ. 112(2), 548–569 (2008)

    Article  Google Scholar 

  • Boysen, N., Stephan, K.: The deterministic product location problem under a pick-by-order policy. Discrete Appl. Math. 161(18), 2862–2875 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  • Chen, F., Wang, H., Qi, C., Xie, Y.: An ant colony optimization routing algorithm for two order pickers with congestion consideration. Comput. Ind. Eng. 66(1), 77–85 (2013)

    Article  Google Scholar 

  • Chen, F., Wang, H., Xie, Y., Qi, C.: An ACO-based online routing method for multiple order pickers with congestion consideration in warehouse. J. Intell. Manuf. (In press). doi: 10.1007/s10845-014-0871-1

  • Colorni, A., Dorigo, M., Maniezzo, V.: Distributed optimization by ant colonies. In: Proceedings of ECAL91—European Conference on Artificial Life, pp. 134–142. Paris (France), (1991). http://faculty.washington.edu/paymana/swarm/colorni92-ecal.pdf Accessed Sept 2014

  • Coyle, J.J., Bardi, E.J., Langley, C.J.: The Management of Business Logistics. West Publishing Company, Mason (1996)

    Google Scholar 

  • Dallari, F., Marchet, G., Melacini, M.: Design of order picking system. Int. J. Adv. Manuf. Technol. 42(1–2), 1–12 (2009)

    Article  Google Scholar 

  • de Koster, R., Le-Duc, T., Jan Roodbergen, K.: Design and control of warehouse order picking: a literature review. Eur. J. Oper. Res. 182, 481–501 (2007)

    Article  MATH  Google Scholar 

  • Dorigo, M., Maniezzo, V., Colorni, A.: The ant system: optimization by a colony of cooperating agents. IEEE Trans. Syst. Man Cybern. Part B 26(1), 1–13 (1996)

    Article  Google Scholar 

  • ESTECO.: MOSA—multi objective simulated annealing. Technical Report 2003-003 (2003).

    Google Scholar 

  • Garetti, M., Taisch, M.: Neural networks in production planning and control. Prod. Plan. Control 10(4), 324–339 (1999)

    Article  Google Scholar 

  • Goldberg, D.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)

    MATH  Google Scholar 

  • Grosse, E.H., Glock, C.H., Ballester-Ripoll, R.: A simulated annealing approach for the joint order batching and order picker routing problem with weight restrictions. Int. J. Oper. Quant. Manage. 2(20), 65–83 (2014)

    Google Scholar 

  • Hall, R.W.: Distance approximation for routing manual pickers in a warehouse. IIE Trans. 25, 77–87 (1993)

    Article  Google Scholar 

  • Ho, Y.-C., Chien, S.-P.: A comparison of two zone-visitation sequencing strategies in a distribution centre. Comput. Ind. Eng. 50(4), 426–439 (2006)

    Article  Google Scholar 

  • Ho, Y.-C., Tseng, Y.-Y.: A study on order-batching methods of order-picking in a distribution centre with two cross-aisles. Int. J. Prod. Res. 44(17), 3391–3417 (2006)

    Article  MATH  Google Scholar 

  • Holland, J.: Adaptation in Natural and Artificial Systems. University of Michigan Press, USA (1975)

    Google Scholar 

  • Hong, S., Johnson, A.L., Peters, B.A.: Batch picking in narrow-aisle order picking systems with consideration for picker blocking. Eur. J. Oper. Res. 221(3), 557–570 (2012)

    Article  MATH  Google Scholar 

  • Hsu, C.-M., Chen, K.-Y., Chen, M.-C.: Batching orders in warehouses by minimizing travel distance with genetic algorithms. Comput. Ind. 56(2), 169–178 (2005)

    Google Scholar 

  • Jarvis, J.M., McDowell, E.D.: Optimal product layout in an order picking warehouse. IIE Trans. 23(1), 93–102 (1991)

    Article  Google Scholar 

  • Kennedy, J., Eberhart, R.: Particle swarm optimization. Proc. IEEE Int. Conf. Neural Networks 4, 1942–1948 (1995). doi:10.1109/ICNN.1995.488968

    Google Scholar 

  • Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Optimization by simulated annealing. Science 220(4598), 671–680 (1983)

    Article  MATH  MathSciNet  Google Scholar 

  • Kuo, R.J., Tseng, W.L., Tien, F.C., Warren Liao, T.: Application of an artificial immune system-based fuzzy neural network to a RFID-based positioning system. Comput. Ind. Eng. 63, 943–956 (2012)

    Article  Google Scholar 

  • Kuo, R.J., Shieh, M.C., Zhang, J.W., Chen, K.Y.: The application of an artificial immune system-based back-propagation neural network with feature selection to an RFID positioning system. Robot. Comput. Integr. Manuf. 29, 431–438 (2013)

    Article  Google Scholar 

  • Kuo, R.J., Hung, S.Y., Cheng, W.C.: Application of an optimization artificial immune network and particle swarm optimization-based fuzzy neural network to an RFID-based positioning system. Inf. Sci. 262, 78–98 (2014)

    Article  Google Scholar 

  • Luxhøj, J.T., Riis, J.O., Stensballe, B.: A hybrid econometric-neural network modeling approach for sales forecasting. Int. J. Prod. Econ. 43, 175–192 (1996)

    Article  Google Scholar 

  • Matusiak, M., De Koster, R., Kroon, L., Saarinen, J.: A fast simulated annealing method for batching precedence-constrained customer orders in a warehouse. Eur. J. Oper. Res. 236(3), 968–977 (2014)

    Article  MATH  Google Scholar 

  • McCulloch, W., Pitts, W.: A logical calculus of the ideas immanent in nervous activity. Bull. Math. Biophys. 5, 115–133 (1943)

    Article  MATH  MathSciNet  Google Scholar 

  • Muppani, V.R., Adil, G.K.: Efficient formation of storage classes for warehouse storage location assignment: a simulated annealing approach. Omega 36(4), 609–618 (2008)

    Article  Google Scholar 

  • Oke, A., Long, M.: An analysis of the downstream logistics operations of a South African FMCG producer. Int. J. Prod. Econ. 108(1–2), 176–182 (2007)

    Article  Google Scholar 

  • Onut, S., Tuzkaya, U.R., Dogac, B.: A particle swarm optimization algorithm for the multiple-level warehouse layout design problem. Comput. Ind. Eng. 54(4), 783–799 (2008)

    Article  Google Scholar 

  • ÖztürkoÄŸlu, Ö., Gue, K.R., Meller, R.D.: A constructive aisle design model for unit-load warehouses with multiple pickup and deposit points. Euro. J. Oper. Res. 236(1), 382–394 (2014)

    Google Scholar 

  • Parikh, P.J., Meller, R.D.: Estimating picker blocking in wide-aisle order picking systems. IIE Trans. 41(3), 232–246 (2009)

    Article  Google Scholar 

  • Petersen, C.G.: The impact of routing and storage policies on warehouse efficiency. Int. J. Oper. Prod. Manage. 19(10), 1053–1064 (1999)

    Article  Google Scholar 

  • Petersen, C.G., Aase, G.: A comparison of picking, storage, and routing policies in manual order picking. Int. J. Prod. Econ. 92, 11–19 (2004)

    Article  Google Scholar 

  • Pourakbar, M., Sleptchenko, A., Dekker, R.: The floating stock policy in fast moving consumer goods supply chains. Transp. Res. Part E: Logistics Transp. Rev. 45(1), 39–49 (2009)

    Article  Google Scholar 

  • Roodbergen, K.J., De Koster, R.: Routing methods for warehouses with multiple cross aisles. Int. J. Prod. Res. 39(9), 1865–1883 (2001)

    Article  MATH  Google Scholar 

  • Rouwenhorst, B., Reuter, B., Stockrahm, V., van Houtum, G.J., Mantel, R.J., Zijm, W.H.M.: Warehouse design and control: framework and literature review. Eur. J. Oper. Res. 122, 515–533 (2000)

    Article  MATH  Google Scholar 

  • Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning representations by back-propagating errors. Nature 323, 533–536 (1986)

    Article  Google Scholar 

  • Schalkoff, R.J.: Artificial neural networks. McGraw-Hill, New York (1997)

    MATH  Google Scholar 

  • Shervais, S., Shannon, T.T., Lendaris, G.G.: Intelligent supply chain management using adaptive critic learning. IEEE Trans. Syst. Man Cybern—Part A: Syst. Humans 33(2), 235–244 (2003)

    Google Scholar 

  • Silva, C.A., Sousa, J.M.C., Runkler, T.A.: Rescheduling and optimization of logistic processes using GA and ACO. Eng. Appl. Artif. Intell. 21(3), 343–352 (2008)

    Article  Google Scholar 

  • Su, C.T.: Intelligent Control Mechanism of part picking operations of automated warehouse. In: Proceedings of the International IEEE/IAS Conference on Industrial Automation and Control: Emerging Technologies pp. 256–261, Taipei, 22–27 May 1995 (1995). doi: 10.1109/IACET.1995.527572

  • Tompkins, J.A., White, J.A., Bozer, Y.A., Frazelle, E.H., Tanchoco, J.M.A., Trevino, J.: Facilities Planning, 2nd edn. Wiley, New York (1996)

    Google Scholar 

  • Wang, Y., Zheng, J., Wang, S.: Evolutionary algorithm inspired particle swarm optimization (EA-PSO) for warehouse allocation problem. In: Proceedings of the 3rd International Conference on Computer Research and Development (ICCRD2011), Shanghai (China), 11–13 March 2011, (2011). doi: 10.1109/ICCRD.2011.5764079

  • Xing, B., Gao, W.-J., Nelwamondo, F.V., Battle, K., Marwala, T.: Ant colony optimization for automated storage and retrieval system. In: IEEE Congress on Evolutionary Computation (CEC), Barcelona (Spain), 18–23 July 2010, (2010a). doi: 10.1109/CEC.2010.5586237

  • Xing, B., Gao, W.-J., Battle, K., Marwala, T., Nelwamondo, F.V.: Intelligent travel route planning for bridge crane type of material handling equipment in cellular manufacturing. In: Proceedings of the IEEE International Conference on Systems Man and Cybernetics (SMC), Istanbul (Turkey), 10–13 Oct. 2010, (2010b). doi: 10.1109/ICSMC.2010.5641894

  • Xinmin, Z., Xiangzhuo, K., Xiaoguang, H., 2008. Modeling and optimizing fixed shelf order-picking for AS/RS based on least time. In: Proceedings of the IEEE International Conference on Automation and Logistics, Qingdao (China), 1–3 Sept 2008. doi: 10.1109/ICAL.2008.4636249

  • Yao, M.-J., Chu, W.-M.: A genetic algorithm for determining optimal replenishment cycles to minimize maximum warehouse space requirements. Omega 36(4), 619–631 (2008)

    Article  Google Scholar 

  • Yu, M.: Enhancing warehouse performance by efficient order picking. Ph.D. thesis—Rotterdam School of Management, Erasmus University (2005). http://repub.eur.nl/pub/13691/EPS2008139LIS9058921673YU.pdf Accessed Sept 2014

  • Zhang, X., Ma, T., Han, X.: Optimizing fixed shelf order-picking for AS/RS based on immune particle swarm optimization algorithm. In: Proceedings of the IEEE International Conference on Automation and Logistics (ICAL 2007), Jinan (China), 18–21 Aug 2007. doi: 10.1109/ICAL.2007.4339062

  • Zhang, G.Q., Lai, K.K.: Combining path relinking and genetic algorithms for the multiple-level warehouse layout problem. Eur. J. Oper. Res. 169(2), 413–425 (2006)

    Article  MATH  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Department of Industrial Engineering, University of Parma, Parco Area Delle Scienze 181/a, 43124, Parma, Italy

    Eleonora Bottani, Roberto Montanari & Giuseppe Vignali

  2. Interdepartmental Centre for Packaging (CIPACK), C/O Department of Industrial Engineering, University of Parma, Parco Area Delle Scienze 181/a, 43124, Parma, Italy

    Marta Rinaldi

Authors
  1. Eleonora Bottani
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  2. Roberto Montanari
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  3. Marta Rinaldi
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  4. Giuseppe Vignali
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Correspondence to Eleonora Bottani .

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Editors and Affiliations

  1. Department of Industrial Engineering Management Faculty, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Istanbul Technical University Management Faculty, Istanbul, Turkey

    Sezi Çevik Onar

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Bottani, E., Montanari, R., Rinaldi, M., Vignali, G. (2015). Intelligent Algorithms for Warehouse Management. In: Kahraman, C., Çevik Onar, S. (eds) Intelligent Techniques in Engineering Management. Intelligent Systems Reference Library, vol 87. Springer, Cham. https://doi.org/10.1007/978-3-319-17906-3_25

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  • DOI: https://doi.org/10.1007/978-3-319-17906-3_25

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