A Queuing Model to Reduce Energy Consumption and Pollutants Production through Transportation Vehicles in Green Supply Chain Management

Amir Azizi

Faculty of Manufacturing Engineering, University of Malaysia Pahang, Pekan, Pahang Darul Makmur, Malaysia.

Yones Yarmohammadi *

Department of Management and Accounting, Allame Tabatabai University, Tehran, Iran.

Ali Yasini

Department of Management, Faculty of Humanities, Ilam University, Ilam, Iran.

Amirhosein Sadeghifard

Department of Management, Ilam Islamic Azad University, Iran.

*Author to whom correspondence should be addressed.


Abstract

Aims: The main goal of this study is to minimize the function with coefficient c, which minimizes vehicles' transportation time and waiting time in supply chain centers.
Study Design: Environmental pollution and shortage of nonrenewable energy resources have increased governments and people's concerns in consuming green products. Queuing and transportation theories have been used in order to reduce energy consumption in a green supply chain.
Methodology: Queuing modeling was performed using LINDO Software. In order to validate the designed model, transportation data of an Iranian dairy products company was used.
Results: The results showed that proper allocation of the present vehicles with certain capacities and employment of queuing theory in the green supply chain caused the reduction of energy consumption through optimizing transportation and waiting times in the green supply chain.
Conclusion: Green products are the result of green supply chain management in organizations' performing strategies in order to reduce waste and environmental pollutants and take a step towards saving energy resources.

Keywords: Green supply chain, energy consumption, transportation, queuing theory optimization, pollution


How to Cite

Azizi, Amir, Yones Yarmohammadi, Ali Yasini, and Amirhosein Sadeghifard. 2015. “A Queuing Model to Reduce Energy Consumption and Pollutants Production through Transportation Vehicles in Green Supply Chain Management”. Journal of Scientific Research and Reports 5 (7):571-81. https://doi.org/10.9734/JSRR/2015/15376.

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