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Material Handling Equipment Selection using Hybrid Monte Carlo Simulation and Analytic Hierarchy Process

Authors: Amer M. Momani, Abdulaziz A. Ahmed

Abstract:

The many feasible alternatives and conflicting objectives make equipment selection in materials handling a complicated task. This paper presents utilizing Monte Carlo (MC) simulation combined with the Analytic Hierarchy Process (AHP) to evaluate and select the most appropriate Material Handling Equipment (MHE). The proposed hybrid model was built on the base of material handling equation to identify main and sub criteria critical to MHE selection. The criteria illustrate the properties of the material to be moved, characteristics of the move, and the means by which the materials will be moved. The use of MC simulation beside the AHP is very powerful where it allows the decision maker to represent his/her possible preference judgments as random variables. This will reduce the uncertainty of single point judgment at conventional AHP, and provide more confidence in the decision problem results. A small business pharmaceutical company is used as an example to illustrate the development and application of the proposed model.

Keywords: Analytic Hierarchy Process (AHP), Materialhandling equipment selection, Monte Carlo simulation, Multi-criteriadecision making

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1085141

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[1] S. Ray, Introduction to Materials Handling, Daryaganj, Delhi: New Age International, 2008, ch. 1.
[2] J. A. Tompkins. J. A. White, Y. A. Bozer. E. H. Frazelle, J. M. Tanchoco, and J. Trevino, Facilities Planning, 3rd edition, New York: Wiley, 2003, pp. 137-287.
[3] S. Sujono, and R. S. Lashkari, "A multi-objective model of operation allocation and material handling selection in FMS design", International Journal of production economics, vol. 105, pp. 116-133, 2007.
[4] O. Kulak, "A decision support system for fuzzy multi-attribute selection of material handling equipments", Expert Systems with Applications, vol. 29, pp.310-319, 2005.
[5] S. Onut, S. S. Kara, and S. Mert, "Selecting the suitable material handling equipment in the presence of vagueness", International Journal of Advanced Manufacturing Technology, vol. 44, pp. 818-828, 2009.
[6] S. Chakraborty, and D. Banik, "Design of a material handling equipment selection model using analytic hierarchy process", International Journal of Advanced Manufacturing Technology, vol. 28, pp. 1237-1245, 2006.
[7] F. T. S. Chan, R. W. L. lp, and H. Lau, "Integration of expert system with analytic hierarchy process for the design of material handling equipment selection system", Journal of Material Processing Technology, vol. 116, Issues 2-3, pp. 137-145, October 2001.
[8] G. Tuzkaya, B. Gulsun, C. Kahraman, and D. Ozgen, " An integrated fuzzy multi-criteria decision making methodology for material handling equipment selection problem and an application, Expert Systems with Applications, Vol. 37, pp. 2853-2863, 2010.
[9] M. Doumpos, and C. Zopounidis, Multicriteria Decision Aid Classification Methods, NJ: Kluwewr Academic Publishers, 2002, ch. 3&4.
[10] P. Goodwin, and G. Wright, Decision Analysis for Management Judgments, 4the edition, Chichester, UK: Wiley, 2009.
[11] R. S. Lashkari, R. Boparai, and J. Paulo, "Towards an integrated model of operation allocation and material handling selection in cellular manufacturing systems", International Journal of Production Economics, vol. 87, pp. 115-139, 2004.
[12] H. R. Sayarshad, "Using bees algorithm for material handling equipment planning in manufacturing systems", International Journal of Advanced Manufacturing Technology, vol. 48, pp. 1009-1018, 2010.
[13] S. H. L. Mirhosseyni, and P. Webb, " A hybrid fuzzy knowledge-based expert system and genetic algorithm for efficient selection and assignment of material handling equipment", Expert Systems with Applications, Vol. 36, pp. 11875-11887, 2009
[14] R. V. Rao, Decision Making in the Manufacturing Environment, 1st edition, London: Springer-Verlag, 2007, ch. 15.
[15] E. S. Rosenbloom, "A probabilistic interpretation of the final rankings in AHP", European Journal of Operations Research, vol. 96, pp. 371- 378, 1996.
[16] O. S. Vaidya, and S. Kumar, "Analytic hierarchy process: an overview of applications", European Journal of Operations Research, vol. 169, pp. 1-29, 2006.
[17] A. Ishizaka, and A. Labib, "Review of the main developments in the analytic hierarchy process", Expert Systems with Applications, vol. 38, pp. 14336-14345, 2011.
[18] T. L. Saaty, "Decision making with the analytic hierarchy process", International Journal of Service Sciences, vol. 1, No. 1, pp. 83-98, 2008.
[19] R. Banuelas, and J. Antony, "Modified analytic hierarchy process to incorporate uncertainty and managerial aspects", International Journal of Production Research, vol. 42, No. 18, pp. 3851-3872, 2004.
[20] G. Manassero et al, "A new method to cope with decision makers- uncertainty in the equipment selection process", CIRP Annals- Manufacturing Technology, vol. 53, Issue 1, pp. 389-392, 2004.
[21] C. Yu, "A GP-AHP method for solving decision-making fuzzy AHP problems", Computers & Operations Research, vol. 29, pp. 1969-2001, 2002.
[22] P. Jaskowski, S. Biruk, and R. Bucon, "Assesing contractor selection criteria weights with fuzzy method application in group decision environment", Automation in construction, vol. 19, pp. 120-126, 2010.
[23] T. Hsu,and F. F. C. Pan, "Application of Monte Carlo AHP in ranking dental quality attributes", Expert Systems with Applications, vol. 36, pp. 2310-2316, 2009.