Eco Friendly Closed Loop Supply Chain Model Under Fuzzy Conditions
M.V. Madhuri1, N. Ravi Shankar2
1M.V. Madhuri, Assistant Professor, Dept. of Mathematics, Dr L. Bullayya college of Engineering Visakhapatnam (A. P.) India.
2N. Ravi Shankar, professor in Dept. of Applied Mathematics, GIS, GITAM (Deemed to be University), Visakhapatnam (A. P.) India.
Manuscript received on November 10, 2019. | Revised Manuscript received on November 17, 2019. | Manuscript published on 30 November, 2019. | PP: 3737-3751 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8129118419/2019©BEIESP | DOI: 10.35940/ijrte.D8129.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Profits of a business organization can be sustained in the long term when the organization focus on environmental benefits and customer satisfaction along with company’s financial benefit. Customer satisfaction index (CSI) can be increased with minimization of the product delivery time and maximization of the quality. Reduction of carbon emission during product manufacture/remanufacture process contributes to the environmental benefit of the organization. The proposed model is a multi-objective, multi-stage, multi-product eco- friendly closed loop supply chain linear programming problem with four objective functions and various constraints under fuzzy environment. A sub model is formulated as an application to an automobile dealership company in Visakhapatnam, India and an experimental study is done using actual data from the company. Profit margin on sale and service of three types (Type P1, P2and P3) of new cars and sale of two types (Type A and B) of old cars are calculated. From the result analysis we can conclude that increase in the sale of new cars of type P1 and old cars of type A increases the profit margin of the company.
Keywords: Closed Loop Supply Chain Network; Linear Programming; Fuzzy Sets, Linear Fractional Programming.
Scope of the Article: Fuzzy Logics.