The Conceptual Design Model of an Automated Supermarket

Authors: Sathya Narayanan V., Sidharth P., Sanal Kumar. V. R.

Abstract:

The success of any retail business is predisposed by its swift response and its knack in understanding the constraints and the requirements of customers. In this paper a conceptual design model of an automated customer-friendly supermarket has been proposed. In this model a 10-sided, space benefited, regular polygon shaped gravity shelves have been designed for goods storage and effective customer-specific algorithms have been built-in for quick automatic delivery of the randomly listed goods. The algorithm is developed with two main objectives, viz., delivery time and priority. For meeting these objectives the randomly listed items are reorganized according to the critical-path of the robotic arm specific to the identified shop and its layout and the items are categorized according to the demand, shape, size, similarity and nature of the product for an efficient pick-up, packing and delivery process. We conjectured that the proposed automated supermarket model reduces business operating costs with much customer satisfaction warranting a winwin situation.

Keywords: Automated Supermarket, Electronic Shopping, Polygon-shaped Rack, Shortest Path Algorithm for Shopping.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1096741

References:

[1] Sathya Narayanan. V., Sidharth. P., Sanal Kumar. V. R, “Robot Controlled Automated Supermarket Model,” Indian Patent (pending), October, 2014 (5070/CHE/2014).
[2] Goodman. J, “Who Does the Grocery Shopping, and When Do They Do It?” survey by The Time Use Institute,2008.
[3] Environics Research Group “Checking out the Canadian Grocery Shopping Experience” survey by MasterIndexTM May 14-19, 2008.
[4] Agrawal R. and Srikant R. “Mining Sequential Patterns”. In proceedings of the 1995 International Conference Data Engineering,1995, pp-3-14
[5] Christian Bunse H. H., “Choosing The ”Best” Sorting Algorithm For Optimal Energy Consumption.” ICSOFT-International Joint Conference on Software Technologies INSTICC Press, 2009. pp. 199-206.
[6] Floyd, R. W., "Algorithm 97, Shortest Path," Comm. ACM, Vol. 5, No. 6, June 1962, p. 345.
[7] Dijkstra, E. W., "A Note on Two Problems in Connexion with Graphs," NumerischeMathematik, Vol. 1, 1959, pp. 269-271.
[8] Hitchner, L. E., A Comparative Investigation of the Computational Efficiency of Shortest Path Algorithms, Operations Research Center, University of California, Berkeley, Report ORC 68-17, July 1968.
[9] C.A.R. Hoare, “Algorithm 64: Quicksort”. Communications of the ACM,Vol. 4 Issue 7, 1961.pp 321
[10] K.Paramasivam D., "Reordering Algorithm for Minimizing Test Power in VLSI Circuits" Engineering Letters, 14:1,February 2007.
[11] Susan Van Zelst, KarelvanDonselaar, TomvanWoensel,Rob Broekmeulen, JanFransoo, “Logistics drivers for shelf stacking in grocery retail stores: Potential for efficiency improvement” International Journal of Production Economics, 2009 pp 620-632
[12] Ming-Hsien Yang, “An efficient algorithm to allocate shelf space” International Journal of Operational Research, 2001 pp 107-118.
[13] Chih-Ming Hsu, Kai-Ying Chen, Mu-Chen Chen, “Batching orders in warehouses by minimizing travel distance with genetic algorithms” Computers in Industry, 2005 pp 169-178
[14] Jeffrey, S.L., Bradlow, E.T., & Fader, P. An exploratory look at in-store supermarket shopping paths. International Journal of Research in Marketing, 22(4), 2005, pp 395-414.
[15] Farley, J., & Ring, L. W. A stochastic model of supermarket traffic flow. Operational Research, 14,1966, pp555-567.
[16] Batty, M. Agent-based pedestrian modeling. In P. Longley & M. Batty (Eds.), Advanced spatial analysis.2003. ESRI Press.
[17] Ibrahim Cil. Consumption universes based supermarket layout through association rule mining and multidimensional scaling. Expert Systems with Applications.2012. pp 8611-8625.
[18] Punjaisri, K., & Wilson, A. The role of internal branding in the delivery of employee brand promise. Journal of Brand Management, 2007, 15(1), 57–70.