BibTex RIS Kaynak Göster
Yıl 2014, Cilt: 4 Sayı: 1, 9 - 20, 23.07.2016

Öz

Kaynakça

  • Babuska, R., Van Der Veen, P.J., Kaymak, U. (2002). Improved covariance estimation for Gustafson Kessel clustering. In Proceedings of the IEEE International Conference on Fuzzy Systems (pp 1081-1085). Honolulu, Hawaii.
  • Ballou, R. (1999). Business Logistics Management. Prentice-Hall Inc, Fourth edition.
  • Balasko, B., Aboyni, J., Feil, B. (2005). Fuzzy clustering and data analysis toolbox. Available at: http://www.fmt.vein.hu/softcomp/ fclusttoolbox.
  • Beasley, J. E. (1990). OR-Library: distributing test problems by electronic mail. Journal of the Operational Research Society (pp. 1069-1072).
  • Bezdek, J.C., Dunn, J.C., (1975). Optimal fuzzy partitions: A heuristic for estimating the parameters in a mixture of normal distributions. IEEE Transactions on Computers (pp. 835-838).
  • Bouzembrak, Y., Allaoui, , H., Goncalves, , G., Bouchriha, , H. (2011). A Multi-Objective Green Supply Chain Network Design. 4th International Conference on Logistics (LOGISTIQUA) (pp. 357-361).
  • Diabat, A. and Simchi-Levi, D. (2009). A Carbon-Capped Supply Chain Network Problem. IEEE International Conference on Industrial Engineering and Engineering Management (pp. 523-527).
  • Doring, C., Lesot, M., Kruse, R. (2006). Data analysis with fuzzy clustering methods. Computational Statistics & Data Analysis, Vol.51 (pp. 192-214).
  • Esnaf, Ş., Küçükdeniz, T. (2009). A Fuzzy Clustering-Based Hybrid Method for a Multi-Facility Location Problem. Journal of Intelligent Manufacturing, Vol.20, No:2 (pp. 259-265).
  • Farahani, R.Z. ve Hekmatfar, , M. (2009). Facility Location: Concepts, Models, Algorithms and Case Studies. Springer-Verlag, Heidelberg.
  • Farahani, R.Z., Steadieseifi, M., Asgari, N. (2010). Multiple Criteria Facility Location Problem:A Survey. Applied Mathematical Modelling, Vol.34 (pp. 1689-1709).
  • Govindan, K., Kannan, D., (2010). A Bi Objective Reverse Logistics Network Design Model. International Conference on Computers & Industrial Engineering (CIE).
  • Gustafson, D.E., Kessel, W.C. (1979). Fuzzy clustering with fuzzy covariance matrix. In Proceedings of the IEEE (pp. 761-766). CDC, San Diego.
  • Harris, I., Mumford, C., Naim, M. (2009). The Multi-Objective Uncapacitated Facility Location Problem for Green Logistics. IEEE Congress on Evolutionary Computation.
  • Harris, I., Naim, M., Palmer, A., Potter, A., Mumford, C. (2011). Assessing the impact of cost optimization based on infrastructure modelling on CO2 emissions. International Journal of Production Economics, Vol. 131, Issue 1, (pp. 313-321).
  • Hoppner, F., Klawonn, F., Kruse, R. and Runkler, T. (1999). Fuzzy Cluster Analysis: methods for classification, data analysis, and image recognition. John Wiley&Sons.
  • Iakovou, E., Vlachos, D., Chatzipanagioti, M., Mallidis, I., (2010). A Comprehensive Optimisation Framework for Sustainable Supply Chain Networks. In Seventh International Conference on Logistics and Sustainable Transport, Slovenia.
  • Jain, A.K., Murty, M.N., Flynn, P.J. (1999). Data Clustering: A Review. ACM Computing Surveys, Vol.31, No.3, (pp.264-323).
  • Kenesei, T., Balasko, B. and Abony, J. (2006). A MATLAB toolbox and its web based variant for fuzzy cluster analysis. In Proceedings of the 7th International Symposium on Hungarian Researchers on Computational Intelligence, November 24–25, Budapest, Hungary.
  • Küçükdeniz T, Baray A, Ecerkale K, Esnaf Ş. (2012). Integrated use of fuzzy c-means and convex programming for capacitated multi-facility location problem. Expert Systems with Applications, Vol. 39, No.4, (pp. 4306-4314).
  • Li, F., Liu, T., Zhang, H., Cao, R., Ding, W., Fasano, J.P. (2008). Distribution center location for green supply chain. International Conference on Service Operations and Logistics, and informatics (IEEE) (pp. 2951–2956).
  • McMichael, A.J., Woodruff, R.E., Hales, S. (2006). Climate change and human health: present and future risks. Lancet, Vol. 367, Issue 9513, (pp. 859-869)
  • Osman, I. H. and Christofides, N. (1994). “Capacitated clustering problems by hybrid simulated annealing and tabu search”, International Transactions in Operational Research, Vol.1, No. 3, pp. 317-336.
  • Paksoy, T., Özceylan, E., Weber, G-W. (2011). A Multi Objective Model for Optimization of a Green Supply Chain. Global Journal of Technology and Optimization, Vol. 2, (pp. 84-96).
  • Pan, S., Ballot, E., Fontane, F. (2009). The reduction of greenhouse gas emissions from freight transport by merging supply chains. International Conference of Industrial Engineering and Systems Managment, IESM, Montreal, Canada.
  • Ramudhin, A., Chaabane, A., Kharoune, M., Paquet, M. (2008). Carbon Market Sensitive Green Supply Chain Network Design. IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1093–1097).
  • Santibanez-Gonzalez, E., Del, R., Robson Mateus, G., Pacca Luna, H. (2011). Solving a public sector sustainable supply chain problem: A Genetic Algorithm approach. In: Proc. of Int. Conf. of Artificial Intelligence (ICAI) (pp. 507–512), Las Vegas, USA.
  • Shaw, K., Shankara, R., Yadava, S.S., Thakurb, L.S., (2012). Modeling a low-carbon garment supply chain, Production Planning & Control (pp. 1-15).
  • Sule, D.R. (2001), “Logistics of Facility Location and Allocation”, Marcel Dekker Inc., New York Wang, F, Lai, X., Shi, N. (2011). A Multi-Objective Optimization for Green Supply Chain Network Design. Decision Support Systems, Vol. 51, (pp. 262–269).
  • WRI-WBCSD GHG Protocol Initiative, Mobile Combustion CO2 Emissions Calculation Tool. June 2003. Version 1.2, available at: http://www.scribd.com/doc/8676658/Mobile-Combustion-CO2-Emissions-Calculation-Tool Wu, H.-J. and Dunn, S. (1995). Environmentally responsible logistics systems. International Journal of Physical Distribution & Logistics Management, Vol. 25 No. 2, (pp. 20-38).
  • Xiaoli, L., Jun, W., Jun, L. (2010). Research on the Optimization of Carbon emissions of Distribution Centers Location Decision. International Conference on Communications, Circuits and Systems (ICCCAS) (pp. 87-89)
  • Yurimoto, S. and Katayama, N. (2002). A Model for the Optimal Number and Locations of Public Distribution Centers and Its Application to the Tokyo Metropolitan Area. International Journal of Industrial Engineering: Theory, Applications and Practice, Vol. 9, (pp. 363-371).

Carbon Emission Based Optimisation Approach for the Facility Location Problem

Yıl 2014, Cilt: 4 Sayı: 1, 9 - 20, 23.07.2016

Öz

In today’s global competitive economy, companies should create value for customer and create value for environment to protect their competitive strengths and/or obtain competitive advantages. Creation of value depends on developing strategic approaches like determining carbon emission level to consider environmental effects. Furthermore, the financial incentives and governmental pressures on companies to reduce their emissions force companies to change and optimize their internal and external processes in order to reduce their greenhouse gas emissions. In this paper, a carbon emission based facility location problem is discussed. A new hyrid method that aims to reduce the amount of CO2 emission in distribution network is presented. Fuzzy C-Means and Gustafson-Kessel algorithms are used to perform clustering analyses. This is followed by the selection of appropriate facility location through the minimization of CO2 emission levels resulting from transportation activities between the facilities and customers by using the emission based center of gravity method which is a new method developed from classical center of gravity method

Kaynakça

  • Babuska, R., Van Der Veen, P.J., Kaymak, U. (2002). Improved covariance estimation for Gustafson Kessel clustering. In Proceedings of the IEEE International Conference on Fuzzy Systems (pp 1081-1085). Honolulu, Hawaii.
  • Ballou, R. (1999). Business Logistics Management. Prentice-Hall Inc, Fourth edition.
  • Balasko, B., Aboyni, J., Feil, B. (2005). Fuzzy clustering and data analysis toolbox. Available at: http://www.fmt.vein.hu/softcomp/ fclusttoolbox.
  • Beasley, J. E. (1990). OR-Library: distributing test problems by electronic mail. Journal of the Operational Research Society (pp. 1069-1072).
  • Bezdek, J.C., Dunn, J.C., (1975). Optimal fuzzy partitions: A heuristic for estimating the parameters in a mixture of normal distributions. IEEE Transactions on Computers (pp. 835-838).
  • Bouzembrak, Y., Allaoui, , H., Goncalves, , G., Bouchriha, , H. (2011). A Multi-Objective Green Supply Chain Network Design. 4th International Conference on Logistics (LOGISTIQUA) (pp. 357-361).
  • Diabat, A. and Simchi-Levi, D. (2009). A Carbon-Capped Supply Chain Network Problem. IEEE International Conference on Industrial Engineering and Engineering Management (pp. 523-527).
  • Doring, C., Lesot, M., Kruse, R. (2006). Data analysis with fuzzy clustering methods. Computational Statistics & Data Analysis, Vol.51 (pp. 192-214).
  • Esnaf, Ş., Küçükdeniz, T. (2009). A Fuzzy Clustering-Based Hybrid Method for a Multi-Facility Location Problem. Journal of Intelligent Manufacturing, Vol.20, No:2 (pp. 259-265).
  • Farahani, R.Z. ve Hekmatfar, , M. (2009). Facility Location: Concepts, Models, Algorithms and Case Studies. Springer-Verlag, Heidelberg.
  • Farahani, R.Z., Steadieseifi, M., Asgari, N. (2010). Multiple Criteria Facility Location Problem:A Survey. Applied Mathematical Modelling, Vol.34 (pp. 1689-1709).
  • Govindan, K., Kannan, D., (2010). A Bi Objective Reverse Logistics Network Design Model. International Conference on Computers & Industrial Engineering (CIE).
  • Gustafson, D.E., Kessel, W.C. (1979). Fuzzy clustering with fuzzy covariance matrix. In Proceedings of the IEEE (pp. 761-766). CDC, San Diego.
  • Harris, I., Mumford, C., Naim, M. (2009). The Multi-Objective Uncapacitated Facility Location Problem for Green Logistics. IEEE Congress on Evolutionary Computation.
  • Harris, I., Naim, M., Palmer, A., Potter, A., Mumford, C. (2011). Assessing the impact of cost optimization based on infrastructure modelling on CO2 emissions. International Journal of Production Economics, Vol. 131, Issue 1, (pp. 313-321).
  • Hoppner, F., Klawonn, F., Kruse, R. and Runkler, T. (1999). Fuzzy Cluster Analysis: methods for classification, data analysis, and image recognition. John Wiley&Sons.
  • Iakovou, E., Vlachos, D., Chatzipanagioti, M., Mallidis, I., (2010). A Comprehensive Optimisation Framework for Sustainable Supply Chain Networks. In Seventh International Conference on Logistics and Sustainable Transport, Slovenia.
  • Jain, A.K., Murty, M.N., Flynn, P.J. (1999). Data Clustering: A Review. ACM Computing Surveys, Vol.31, No.3, (pp.264-323).
  • Kenesei, T., Balasko, B. and Abony, J. (2006). A MATLAB toolbox and its web based variant for fuzzy cluster analysis. In Proceedings of the 7th International Symposium on Hungarian Researchers on Computational Intelligence, November 24–25, Budapest, Hungary.
  • Küçükdeniz T, Baray A, Ecerkale K, Esnaf Ş. (2012). Integrated use of fuzzy c-means and convex programming for capacitated multi-facility location problem. Expert Systems with Applications, Vol. 39, No.4, (pp. 4306-4314).
  • Li, F., Liu, T., Zhang, H., Cao, R., Ding, W., Fasano, J.P. (2008). Distribution center location for green supply chain. International Conference on Service Operations and Logistics, and informatics (IEEE) (pp. 2951–2956).
  • McMichael, A.J., Woodruff, R.E., Hales, S. (2006). Climate change and human health: present and future risks. Lancet, Vol. 367, Issue 9513, (pp. 859-869)
  • Osman, I. H. and Christofides, N. (1994). “Capacitated clustering problems by hybrid simulated annealing and tabu search”, International Transactions in Operational Research, Vol.1, No. 3, pp. 317-336.
  • Paksoy, T., Özceylan, E., Weber, G-W. (2011). A Multi Objective Model for Optimization of a Green Supply Chain. Global Journal of Technology and Optimization, Vol. 2, (pp. 84-96).
  • Pan, S., Ballot, E., Fontane, F. (2009). The reduction of greenhouse gas emissions from freight transport by merging supply chains. International Conference of Industrial Engineering and Systems Managment, IESM, Montreal, Canada.
  • Ramudhin, A., Chaabane, A., Kharoune, M., Paquet, M. (2008). Carbon Market Sensitive Green Supply Chain Network Design. IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1093–1097).
  • Santibanez-Gonzalez, E., Del, R., Robson Mateus, G., Pacca Luna, H. (2011). Solving a public sector sustainable supply chain problem: A Genetic Algorithm approach. In: Proc. of Int. Conf. of Artificial Intelligence (ICAI) (pp. 507–512), Las Vegas, USA.
  • Shaw, K., Shankara, R., Yadava, S.S., Thakurb, L.S., (2012). Modeling a low-carbon garment supply chain, Production Planning & Control (pp. 1-15).
  • Sule, D.R. (2001), “Logistics of Facility Location and Allocation”, Marcel Dekker Inc., New York Wang, F, Lai, X., Shi, N. (2011). A Multi-Objective Optimization for Green Supply Chain Network Design. Decision Support Systems, Vol. 51, (pp. 262–269).
  • WRI-WBCSD GHG Protocol Initiative, Mobile Combustion CO2 Emissions Calculation Tool. June 2003. Version 1.2, available at: http://www.scribd.com/doc/8676658/Mobile-Combustion-CO2-Emissions-Calculation-Tool Wu, H.-J. and Dunn, S. (1995). Environmentally responsible logistics systems. International Journal of Physical Distribution & Logistics Management, Vol. 25 No. 2, (pp. 20-38).
  • Xiaoli, L., Jun, W., Jun, L. (2010). Research on the Optimization of Carbon emissions of Distribution Centers Location Decision. International Conference on Communications, Circuits and Systems (ICCCAS) (pp. 87-89)
  • Yurimoto, S. and Katayama, N. (2002). A Model for the Optimal Number and Locations of Public Distribution Centers and Its Application to the Tokyo Metropolitan Area. International Journal of Industrial Engineering: Theory, Applications and Practice, Vol. 9, (pp. 363-371).
Toplam 32 adet kaynakça vardır.

Ayrıntılar

Diğer ID JA56HA22RM
Bölüm Makaleler
Yazarlar

Sinem Büyüksaatçı Bu kişi benim

Şakir Esnaf Bu kişi benim

Yayımlanma Tarihi 23 Temmuz 2016
Yayımlandığı Sayı Yıl 2014 Cilt: 4 Sayı: 1

Kaynak Göster

APA Büyüksaatçı, S., & Esnaf, Ş. (2016). Carbon Emission Based Optimisation Approach for the Facility Location Problem. TOJSAT, 4(1), 9-20.
AMA Büyüksaatçı S, Esnaf Ş. Carbon Emission Based Optimisation Approach for the Facility Location Problem. TOJSAT. Temmuz 2016;4(1):9-20.
Chicago Büyüksaatçı, Sinem, ve Şakir Esnaf. “Carbon Emission Based Optimisation Approach for the Facility Location Problem”. TOJSAT 4, sy. 1 (Temmuz 2016): 9-20.
EndNote Büyüksaatçı S, Esnaf Ş (01 Temmuz 2016) Carbon Emission Based Optimisation Approach for the Facility Location Problem. TOJSAT 4 1 9–20.
IEEE S. Büyüksaatçı ve Ş. Esnaf, “Carbon Emission Based Optimisation Approach for the Facility Location Problem”, TOJSAT, c. 4, sy. 1, ss. 9–20, 2016.
ISNAD Büyüksaatçı, Sinem - Esnaf, Şakir. “Carbon Emission Based Optimisation Approach for the Facility Location Problem”. TOJSAT 4/1 (Temmuz 2016), 9-20.
JAMA Büyüksaatçı S, Esnaf Ş. Carbon Emission Based Optimisation Approach for the Facility Location Problem. TOJSAT. 2016;4:9–20.
MLA Büyüksaatçı, Sinem ve Şakir Esnaf. “Carbon Emission Based Optimisation Approach for the Facility Location Problem”. TOJSAT, c. 4, sy. 1, 2016, ss. 9-20.
Vancouver Büyüksaatçı S, Esnaf Ş. Carbon Emission Based Optimisation Approach for the Facility Location Problem. TOJSAT. 2016;4(1):9-20.