Multi-Objective Restricted Solid Transportation Problem in Intuitionistic Fuzzy Environment with Emission Cost
P. Vijayalakshmi1, J. Merline Vinotha2
1P. Vijayalakshmi, Hindusthan Institute of Technology, Coimbatore (Tamil Nadu), India.
2J. Merline Vinotha, Holy Cross College Autonomous, Trichy (Tamil Nadu), India.
Manuscript received on 20 July 2019 | Revised Manuscript received on 03 August 2019 | Manuscript Published on 10 August 2019 | PP: 722-727 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B11340782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1134.82S319
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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: Transportation plays key role in logistic and supply chain management for decreasing cost and enhances service. The transport sector contributes 23% of the total CO2 emissions in the world according to the latest estimates of the International Energy Agency (IEA).There is a direct link between weight of the quantity transported and co2 emission for the freight transport. This paper presents multi objective restricted solid transportation problem in intuitionistic fuzzy ambiance with emission cost which is based on weight of the quantity transported and vehicle cost under some restriction on transported amount. An extra constraint on the total budget at each destination is imposed. Transportation models are formulated under crisp and fuzzy environments and fuzzy models are converted into crisp using average method. The total time and emission cost based on weight of the quantity transported for restricted and unrestricted models are compared. The optimal solution is obtained by using weighted sum method and Lingo 13.0 Software. Mathematical example is given to validate the proposed model.
Keywords: Multi-Objective, Solid Transportation Problem, Budget Constraint, Atanassov’s Intuitionist Fuzzy Number, Emission Cost.
Scope of the Article: Transportation Engineering