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     Research Journal of Applied Sciences, Engineering and Technology


Enhancing Economical, Environmental and Social Objectives through Leasing Services

1Alireza Noorbakhsh, 2Sajjad Shokohyar and 3Armin Aalirezaei
1Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy
2Department of Information Management, Shahid Beheshti University, G.C., Tehran, Iran
3Department of Industrial Engineering, Semnan University, Semnan, Iran
Research Journal of Applied Sciences, Engineering and Technology   2015  10:1124-1138
http://dx.doi.org/10.19026/rjaset.11.2127  |  © The Author(s) 2015
Received: July ‎2, ‎2015  |  Accepted: August ‎2, ‎2015  |  Published: December 05, 2015

Abstract

What human has been doing on earth natural system till now is competitively unfair consuming of limited resources, continuing this trend without thinking of sustainable development caused irreparable destruction. Sustainable leasing is an effective tool for fulfilling consumer’s demands with attaining high level of resources productivity. Current researches are just focused on economical and environmental consideration. Hence in this study; a model is developed to help leasing companies to achieve sustainable development. The objective of this model is to design a sustainable leasing system, in which economical, environmental and social impacts are balanced during leasing and its EOL phase from customers and leasing company point of views. To solve the problem, Multi-Objective Genetic Algorithm (MOGA) has been applied to find the Pareto-optimal solutions. These Pareto-optimal solutions will give some trade off information about the three mentioned objectives. So decision makers can analysis the variability of economical impact in compare to environmental and social improvements. Finally, a company of electronic leasing has been considered for a case study to validate the method and potential applications of the developed model.

Keywords:

End of life, genetic algorithm, leasing, sustainability,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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