sharafi, A., Bashiri, M. (2016). Green Vehicle Routing Problem with Safety and Social Concerns. Journal of Optimization in Industrial Engineering, 10(21), 93-100. doi: 10.22094/joie.2016.264
arghavan sharafi; Mahdi Bashiri. "Green Vehicle Routing Problem with Safety and Social Concerns". Journal of Optimization in Industrial Engineering, 10, 21, 2016, 93-100. doi: 10.22094/joie.2016.264
sharafi, A., Bashiri, M. (2016). 'Green Vehicle Routing Problem with Safety and Social Concerns', Journal of Optimization in Industrial Engineering, 10(21), pp. 93-100. doi: 10.22094/joie.2016.264
sharafi, A., Bashiri, M. Green Vehicle Routing Problem with Safety and Social Concerns. Journal of Optimization in Industrial Engineering, 2016; 10(21): 93-100. doi: 10.22094/joie.2016.264
Green Vehicle Routing Problem with Safety and Social Concerns
1Department of Industrial Engineering, Faculty of Engineering Shahed University, Tehran, Iran
2IE department, Shahed University, Qom Highway, Tehran
Abstract
Over the two last decades, distribution companies have been aware of the importance of paying attention to the all aspects of a distribution system simultaneously to be successful in the global market. These aspects are the economic, the environmental, the social and the safety aspects. In the Vehicle Routing Problem (VRP) literature, the economic issue has often been used, while the environmental, the safety and the social concerns have been less proportion of studies. The Green vehicle routing problem (GVRP) is one of the recent variants of the VRP, dealing with environmental aspects of distribution systems. In this paper, two developed mixed integer programming models are presented for the GVRP with social and safety concerns. Moreover, a Genetic Algorithm (GA) is developed to deal efficiently with the problem in large size. Different numerical analyses have performed to validate the presented algorithm in comparison to exact solutions and investigate the influence of several key factors like the effect of increasing the cost of safety aspect on route balancing, and customer waiting time. The results confirm that the proposed algorithm performs well and has more social and safety benefits (such as more balanced tours and fewer customers waiting time than the classic GVRP.
Highlights
Two developed mixed integer programming models are presented for the Green vehicle routing problem (GVRP) with social and safety concerns.
A Genetic Algorithm (GA) is developed to deal efficiently with the problem in large size.
Different numerical analyses have performed to validate the presented algorithm in comparison to exact solutions
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