Uncertain model of industrial clusters for the optimal arrangement of co-operation networks under sustainable and dynamic conditions

Document Type : Article

Authors

1 Department of Industrial Engineering, Payame Noor University, PO BOX 19395-3697, Tehran, Iran

2 School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

3 - School of Strategy & Leadership, Faculty of Business and Law, Coventry University, Coventry, UK. - Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran.

Abstract

Industrial clusters are one of the most current development models. Aggregation of firms in a geographical area has many advantages, such as cost reduction, better supply, and knowledge emission with linkage together. The linkage result will be created the networks. The industrial clusters without co-operation networking will not be developed. That must be noticed to severe changes of business environment parameters. Therefore, this paper develops an uncertain mathematical model under sustainable and dynamic conditions. The model contains four objectives, namely profit, transportation cost, employment, and environment appraisal of the cluster. The outcome of this research is to find the best/optimal solution for firms’ arrangements with/within networks that maximize the profit, employment, and environment score and so minimize the transportation cost. The assignment patterns show horizontal and vertical cooperation with/within networks. The efficiency of model clustering in sub-clusters is followed by the neighbor clustering efficiency and the one’s clustering efficiency methods.

Keywords

References

References
[1] Caron, H. J. and Pouder, R. W. “Technology Clusters versus Industry Clusters: Resources, Networks, and Regional Advantages”, Growth and Change, 37(2): pp. 141-171 (2006).
[2] Majidi, J. “Cluster or industrial clusters”, Small Industries & Industrial Parks Organization, Tehran (2003).
[3] He, J. and Fallah, M.H. “The typology of technology clusters and its evolution: Evidence from the hi-tech industries”, Technological Forecasting & Social Change, 78(6), pp. 945–952 (2011).
[4] Del-Angizan, S.  “Science and technology clusters toward a common theory”, Journal of Parks and Growth and Technology Centers, 5(2), pp. 16–29 (2011).
[5] Dezfoulian, H.R., Afrazeh, A. and Karimi, B. “A new model to optimize the knowledge exchange in industrial cluster: A case study of Semnan plaster production industrial cluster”, Sciatica Iranica – Transaction E journal, 24(2), pp. 834-846 (2017).
[6] Gordon, I.R. and McCann, P. “Industrial clusters: Complexes, agglomeration and/or social networks?”, Urban Studies, 37(3), pp. 513-532 (2000).
[7] Porter, M.E. “Clusters and the new economics of competition”, Harvard Business Review, 76(6), pp. 77-90 (1998).
[8] Sprenger, R.U. “Inter-firm networks and regional networks opportunities for employment and environmental protection”, Institute for Economic Research (IFO), Munich, (2001).
[9] Glückler, J. and Hammer, I. “Cooperation gains and network goods”, Business Networks Reloaded book, Publisher in Nomos Ashgate, pp. 22-41 (2015).
[10] Lu, R., Reve, T., Huang, J. and et al. “A literature review of cluster theory: Are relations among clusters important?”, Journal of Economic Surveys, 32 (4), pp. 1201-1220 (2018).
[11] Marshall, A. “Principles of economics”, 8th Edition, MacMillan, London (1920).
[12] Krugman, P. “Increasing returns and economic geography”, Journal of Political Economy, 99(3), pp. 483-499 (1991).
[13] Saxenian, A. “Regional advantage: Culture and competition in Silicon Valley and route 128”, MA: Harvard University Press, Cambridge (1994).
[14] Simmie, J. and Sennett, J. “Innovation in the London metropolitan region”, in: D. Hart, J. Simmie, P. Wood, and J. Sennett (Eds.), Innovative clusters and competitive cities in the UK and Europe”, Working Paper, No. 182, Oxford (1999).
[15] Roelandt, T.J. and Den Hertog, P. “Cluster analysis and cluster policy in the Netherlands”, Boosting Innovation: the cluster approach, 31, pp. 9-23 (1999).
[16] Hill, E. and Brennan, J. “A methodology for identifying the drivers of industrial clusters: The foundation of regional competitive advantage”, Economic Development Quarterly, 14(1), pp. 65-96 (2000).
[17] Van den Berg, L., Braun, E. and Van Winden, W. “Growth clusters in European cities: An integral approach”, Urban Studies, 38(1), pp. 185-205 (2001).
[18] Ketels, C. “The development of the cluster concept–present experiences and further developments”, in: NRW Conference on Clusters, Duisberg, Germany, vol. 5 (2003).
[19] OECD, “Organization for economic co-operation and development the DAC guidelines”, Strategies for Sustainable Development, Paris (2001).
[20] Rosenfeld, S.T. “Industry clusters: Business choice, policy outcome, or branding strategy?”, Journal of New Business Ideas and Trends, 3(2), pp. 4-13 (2005).
[21] Cortright, J. “Making sense of clusters: Regional competitiveness and economic development”, Impresa, Inc., The Brookings Institution, 4, pp. 56-62 (2006).
[22] Schilling, M. “Technological innovation management strategies Book”, Mohammad Aerabi and Mohammad Taghi Zade Motlagh, Cultural Research Office, Second edition (2011).
[23] Glaeser, E. and Gottlieb, J. “The wealth of cities: agglomeration economies and spatial equilibrium in the United States”, Journal of Economic Literature, 47(4), pp. 983-1028 (2009).
[24] Wolman, H. and Hincapie, D. “Clusters and cluster-based development: A literature review and policy discussion, Working Paper, George Washington Institute of Public Policy, The George Washington University, pp. 1-45 (2010).
[25] UNIDO “Industrial development report learning and innovation through competing”, Vienna (2003).
[26] Sheffi, Y. “Logistics clusters: delivering value and driving growth”, MIT press (2012).
[27] Delgado, M., Porter, M.E. and Stern, S. “Defining clusters of related industries”, Journal of Economic Geography, 16 (1), pp. 1–38 (2016).
[28] Lu, R., Reve, T., Huang, J. and et al. “A literature review of cluster theory: Are relations among clusters important?”, Journal of Economic Surveys, 32 (4), pp. 1201-1220 (2018).
[29] Sarafrazi, A., Bashiri, M. and Tavakkoli-Moghaddam, R. “Multi-objective modeling of industrial clusters from the perspective of dynamic cellular manufacturing systems and sustainable economic development”, Econometric Modeling Journal, 3(2), pp. 49-91, (2019).
[30] Yu, H., and Solvang, W.D. “A fuzzy-stochastic multi-objective model for sustainable planning of a closed-loop supply chain considering mixed uncertainty and network flexibility”, Journal of Cleaner Production, 266, Art. No. 121702 (2020).
[31] Mohammadia, A.S., Alemtabriza, A., Pishvaeeb , M, and et al. “A multi-stage stochastic programming model for sustainable closed-loop supply chain network design with financial decisions: A case study of plastic production and recycling supply chain”, Scientia Iranica- Transactions E journal, 27(1), pp. 377-395 (2020).
[32] Babu, A.S. “Development of virtual cellular manufacturing systems for SME”, Logistic Information Management, 13(4), pp. 228-243 (2000).
[33] Han, W., Zhao, J.L. and Chen, Y. “A virtual cellular manufacturing system design model based on axiomatic design theory”, Applied mechanics and Materials, 271, pp. 1478-1484 (2012).
[34] Han, W., Liu, J. and Mei, L. “The resource conflict resolution problem for virtual cellular manufacturing inter-cell scheduling under the conditions of resource sharing”, Applied Mechanics and Materials, 527, pp. 286-293 (2014).
[35] Khilwani, N., Ulutas, B.H., Islier A.A. and et al. “A methodology to design virtual cellular manufacturing systems”, Journal of Intelligent Manufacturing, 22, pp. 533–544 (2011).
[36] Rezazadeh, H., Mahini, R. and Zarei, M. “Solving a dynamic virtual cell formation problem by linear programming embedded particle swarm optimization algorithm”, Applied Soft Computing, 11, pp. 3160-3169 (2011).
[37] Renna, P. “Design policies in virtual cellular manufacturing systems by multi-domain simulation environment”, Applied Mechanics and Materials, 718, pp. 192-197 (2015).
[38] Askin, R.G. and Strada, S. “A survey of cellular manufacturing practices”, in: S. Irani (Ed.), Handbook of Cellular Manufacturing Systems, John Wiley, New York (1999).
[39] Safaei, N., Saidi-Mehrabad, M. and Babakhani, M. “Designing cellular manufacturing systems under dynamic and uncertain conditions”, Journal of Intelligent Manufacturing, 18(3), pp. 383-399 (2007).
[40] Hamedi, M., Esmaeilian, G. and Napsiahbt, I. “Developing capability–based virtual cellular manufacturing systems and comparison with capability-based classical cellular manufacturing systems”, Applied Mechanics and Materials, 110, pp. 3938-3946 (2012).
[41] Nomden, G. and van der Zee, D.J. “Virtual cellular manufacturing configuring routing flexibility”, International Journal of Production Economics, 112, pp. 439-451 (2008).
[42] Silva, J.D., Fernandes, V., Limont, M. and Rauen, W.B. “Sustainable development assessment from a capitals perspective: Analytical structure and indicator selection criteria”, Journal of Environmental Management, 260, Article No. 110147 (2020).
[43] Feser, E.J. and Bergman, E.M. “National industry cluster templates: A framework for applied regional cluster analysis”, Regional Studies, 34(1), 1-19 (2000).
[44] Pouya, A. and Ghorbanpor, A. “The clustering of industries in fuzzy environment by green supply chain for environment management”, Urban Management Journal, 39 (9), pp. 71-86 (2014).
[45] Sarayloo, F. and Tavakkoli-Moghaddam, R. “Multi-objective particle Swarm optimization for a dynamic cell formation problem, in: D.S. Huang et al. (Eds.), Proceedings of the 6th Int. Conf. on Intelligent Computing (ICIC), Changsha, China, 18-22 August 2010, CCIS 93, pp., Springer, Heidelberg (2010).
[46] Dimopoulos, C. “Multi-objective optimization of manufacturing cell design”, International Journal of Production Research, 44(22), pp. 4855-4875 (2006).
[47] Zitzler, E. and Thiele, L. “Multi-objective evolutionary algorithms: A comparative case study and the strength Pareto approach”, IEEE Transactions on Evolutionary Computation, 3(4), pp. 257-271 (1999).   
[48] Bajestani, M.A., Rabbani, M., Rahimi-Vahed and et al. “A multi-objective scatter search for a dynamic cell formation problem”, Computers & Operations Research, 36(3), pp. 777–794 (2009).
[49] Shirazi, H., Kia, R., Javadian, N. and Tavakkoli-Moghaddam, R. “An archived multi-objective simulated annealing for a dynamic cellular manufacturing system”, Journal of Industrial Engineering – International, 10(2), 1-17 (2014).
[50] Safaei, N. and Tavakkoli-Moghaddam, R. “Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing systems, International Journal of Production Economics, 120(2), pp. 301-314 (2009).
[51] Kia, R., Shirazi, H., Javadian, N. and Tavakkoli-Moghaddam, R. “A multi-objective model for designing a group layout of a dynamic cellular manufacturing system”, Journal of Industrial Engineering – International, 9(8), pp. 1-14 (2013).
[52] Mahdavi, I., Paydar, M. and Solimanpur, M. “Multi-objective cell formation and production planning in dynamic virtual cellular manufacturing systems”, International Journal of Production Research, 49(21), pp. 6517–6537 (2011).
[53] Ariafar, S., Ismail, N., Tang, S.H. and et al. “Design of a facility layout model in hybrid cellular manufacturing systems under variable demand”, International Journal of Industrial and Systems Engineering, 9(4), pp. 373-387 (2011).
[54] Mavrotas, G. “Effective implementation of the e-constraint method in multi-objective mathematical programming problems”, Applied Mathematics and Computation, 213(2), pp. 455–465 (2009).
[55] Arikan, F. and Gungor, Z. “A parametric model for cell formation and exceptional elements’ problems with fuzzy parameters”, Journal of Intelligent Manufacturing, 16(1), pp. 103-114 (2005).
[56] Yeh, W.C. and Chuang, M.C. “Using multi-objective genetic algorithm for partner selection in green supply chain”, Expert Systems with Applications, 38, pp. 4244-4253 (2011).
[57] Noorossana, R. and Kamali-Ardakani, M. “A weighted metric method to optimize multi-response robust problems”, Journal of Industrial Engineering - International, 8(5), pp. 10-19 (2009).
 [58] Bellman, R.E. and Zadeh, L.A. “Decision Making in a Fuzzy Environment”. Management Sciences, 17, pp. 141-164 (1970).
[59] UNIDO “Development of clusters and networks of SMEs: The UNIDO program, A guide to export consortia”, Vienna, 35 (2005).
Scientia Iranica

Articles in Press, Accepted Manuscript
Available Online from 06 August 2021

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