development of a mathmatical model for evaluating customers of multi-product green supply chain

Document Type : Original Article

Authors
Farzad Masihi 1
Mohammad Taghi Taghavifard 2
ghanbar abbaspour esfeden 3
alireza rashidi komijan 3
1 P.H.D Student in Industrial Management, South Tehran Branch, Islamic Azad University-Tehran, Iran
2 Faculty of Management and Accounting, Allameh Tabatabai University, Tehran, Iran .
3 Faculty of Industrial Engineering, South-Tehran Branch, Islamic Azad University, Tehran, Iran.
Abstract
.In this study, in the form of development, a mathematical model for evaluating customers of a multi-product green supply chain is presented, while practical concepts such as customers are examined by considering green indices. The goals that we will address in this study include minimizing access time for the best customer orientation. One of the basic and important factors in attracting customers is timely delivery time. Another concept that will be examined in this research in the development of mathematical model is the delivery rate. Today, the scope of suppliers' activity in a supply chain includes a wide range of customer needs. Among these cases, upstream currents in the direction of the supplier and downstream currents in the direction of the consumer are considered. Among other things, pay attention to the delivery rate. In this study, three consumer segments are defined based on their buying behavior and green consumers, incompatible consumers and red consumers. A planning model proposed to optimize the supply chain network for a retailer is developed, which includes manufacturers, carriers, and distribution centers based on the green expectations of consumer sectors. In addition, a set of scenarios will be evaluated in order to understand the impact of a higher determinant level on this solution.
Keywords
Keywords: Supply chain
customer classification
uncertainty
environmental indicators
and multi-objective model
  • آذر، ع و فرجی، ح (1390). علم مدیریت فازی، چاپ چهارم، تهران، موسسه کتاب مهربان نشر.
  • آذر، ع؛ محمودیان، ا و هاشمی، م (1395). ارائه روشی به منظور ارزیابی عملکرد زنجیره تأمین سبز پتروشیمی های عسلویه با استفاده از ترکیب روش فازی و مدل سازی غیرخطی. فصل نامه ی مطالعات اقتصاد انرژی/ سال دوازدهم / شماره 48، صفحات 173-193.
  • امیدوار، ر؛ سرداری، ا و یزدانی، ن (1394). رتبه بندی موانع مدیریت زنجیره تأمین سبز با استفاده از روش دیمتل (مطالعه شرکت پارس خودرو( . فصلنامه علمی- پژوهشی تحقیقات بازاریابی نوین سال پنجم، شماره دوم.
  • ایمانی، د و احمدی، ا (1388). مدیریت زنجیره تأمین سبز: راهبرد نوین کسب مزیت رقابتی. نشریه مهندسی خودرو و صنایع وابسته، شماره 1.
  • زاهدی، شمس السادات (1385)، مبانی توریسم و اکوتوریسم پایدار، چاپ سوم، تهران، انتشارات دانشگاه علامه طباطبائی.
  • شائمی، ع؛ خزائی، ج؛ مهدی پور، م و بالوئی، ه (1391). فصلنامه علمی- پژوهشی تحقیقات بازاریابی نوین سال دوم، شماره دوم
  • صفایی قادیکلایی، ع؛ طبیبی، م و حاجی آبادی، ف(1392) .ارائه رویکرد ترکیبی ANP-DEMATEL فازی جهت اولویت‌بندی معیارهای ارزیابی عملکرد تأمین‌کننده سبز: شرکت دیزل سنگین ایران. پژوهش‌های مدیریت در ایران. مقاله 7، دوره 17، شماره 3، پاییز 1392، صفحه 129-149
  • قاضی زاده، مصطفی؛ نوروززاده ،فاطمه و رئیسی قربان آبادی، ح (1393). تجزیه‌وتحلیل مدیریت زنجیره تأمین LARGe با استفاده از تکنیک دیمتل1 در شرکت سایپا
  • Awasthi, A., Chauhan, S.S., Goyal, S.K. (2010). A fuzzy multi criteria approach for evaluating environmental performance of suppliers. International Journal of Production Economics, 126, 370–378.
  • Cebi, F., Otay, I; (2016). A two-stage fuzzy approach for supplier evaluation and order allocation problem with quantity discounts and lead time. Information Sciences.
  • Coskun, S., Ozgur, L., Polat, O., Gungor, A. (2016). A model proposal for green supply chain network design based on consumer segmentation Journal of Cleaner Production 110, 149-157.
  • Fung, T. and Marafa, L.M. (2002). Landscape ecology of Feng Shui woodlands and the potential for ecotourism using IKONOS images and GIS, international Geoscience and Remote sensing Symposium (IGARSS), 6, 3246-3248.
  • Gold, S., Awasthi, A. (2015). Sustainable global supplier selection extended towards sustainability risks from (1+n)th tier suppliers using fuzzy AHP based approach.  IFAC-Papers OnLine, 48-3, 966–971.
  • Greeff, G., & Choshal, R., (2004), . Practical E-Manufacturing and supply chain management.
  • Guillen-Gosalbez, G, and Grossman LE, (2009) “ Optimal design and planning of sustainable chemical supply chains under uncertaintly” ALCHE Journal, 55(1), 99-121.
  • Hammouda G., Saccomanno F., Fu L. (2001), Allocating emergency response facilities to mitigate risks of dangerous goods transportation. The national academies of science. Engineering. Medicine, 1. 363-376.
  • Harris, L. and Andrew, C, (2002); The Greening of Organizational Culture, Journal of Organizational Change Management, 15(3), 214-234.
  • Hashemi HM, Karimi AM, Tavana MJ.(2015). “An integrated green supplier selection approach with analytic network process and improved grey relational analysis”. International Journal of Production Economics,Volume 159, 178–191.
  • Ho, W., Xu, X., Dey, P.K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 22, 16-24.
  • Johnny C. Ho, Maurice K. Shalishali, Tzu-Liang (Bill) Tseng, David S(2009). ”opportunities in green supply chain management”, The Coastal Business Journal, 8(1).
  • Kannan, D., Khodaverdi, R., Olfat, L., Jafarian, A., Diabat, A. (2013). Integrated fuzzy multi criteria decision making method and multi- objective programming approach for supplier selection and order allocation in a green supply chain, Journal of Cleaner Production, 4, 233-264.
  • , Fearon. (1997). Purchasing and supply management. IRWIN. Liao, Z., Rittscher, J. (2007). A multi-objective supplier selection model under stochastic demand conditions. International Journal of Production Economics, 105 (1), 150–159.
  • Lin, R.H. (2009). An integrated FANP-MOLP for supplier evaluation and order allocation. Applied Mathematical Modeling, 33 (6), 2730–2736.
  • Ninlawan C., Seksan P., Tossapol K., Pilada W. (2015). The Implementation of Green Supply Chain, 12th Global Conference on Sustainable Manufacturing – Emerging Potentials. 26,  695-699.
  • Onüt, S., Kara, S.S., Isik, E. (2009). Long-term supplier selection using a combined fuzzy MCDM approach: a case study for a telecommunication company. Expert with Systems Application, 36 (2), 3887–3895.
  • A., Zamani. M., Yazdani-Chamzini. A., Kazimieras Zavadskas. E., (2014), Proposing a new integrated model based on sustainability balanced scorecard (SBSC) and MCDM approaches by using linguistic variables for the performance evaluation of oil producing companies, Expert Systems with Applications 41, 7316–7327.
  • Sabri E.H., Beamon B.M., (2000), A multi-objective approach to simultaneous strategic and operational planning in supply chain design”, Omega, 28(5), 581-598.
  • Tseng, M. L. and Lan, J. C. H. (2010), "Using FANP approach on selection of competitive priorities based on cleaner production implementation: a case study in PCB manufacturer", Clean Technologies and Environmental Policy, 10, 17-29.
  • Xia, W., Wu, Zh., (2007). Supplier selection with multiple criteria in volume discount environments. Omega, 35, 494-504.
  • Yücel, A., Güneri, A.F. (2011). A weighted additive fuzzy programming approach for multi-criteria supplier selection. Expert Systems with Applications 38, 6281–6286.
  • Zhou J., Liu B., (2003). New stochastic models for capacitated location-allocation problem. Computers & Industrial Engineering, 45, 111-125.
  • Zhu,Q.,Sarkis, J and Lai, K (2007) “Green Supply Chain Management:Pressures, Practices and Performance within Chinese Autoomobile Industry” Journal of Cleaner Production 15, 1041-1052.
  • Zouggari, A., Benyoucef, L. (2012). Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem. Engineering Applications of Artificial Intelligence, 25, 507-519.