Abstract
As concern for the environment rises, green logistics is becoming essential and necessary to expand profit margins for companies and improve customer services. As such, companies take into account the external costs of logistics associated mainly with environmental pollution and a possible area of improvement is determined in the context of vehicle utilization. The aforementioned considerations form the background of this paper, which aims to investigate different operational scenarios of a company for urban logistics in an effort to reduce routing and environmental costs. Assuming a homogeneous fleet of capacitated vehicles, the goal is to design minimum cost vehicle routes for the service of a set of geographically scattered customers. The objective is to minimize the number of vehicles required to service all customers and the total mileage in order to indirectly streamline the urban delivery operations related to products. Besides routing costs, the environmental perspective behind this study is captured minimizing the total fuel consumption and thus, the possible pollutant emissions generated. An efficient routing algorithm is proposed utilizing several types of data specifying operational constraints such as vehicle’s capacity, fleet size, location information and customer’s data (i.e. time windows, demand, service time). For the evaluation of the different operational scenarios, an empirical study based on real data is conducted assessing the performance of the proposed algorithm and the reported results demonstrate both operational and environmental impacts.
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Anagnostopoulou, A., Boile, M. (2019). Environmental Aspects of Urban Freight Movement in Private Sector. In: Nathanail, E., Karakikes, I. (eds) Data Analytics: Paving the Way to Sustainable Urban Mobility. CSUM 2018. Advances in Intelligent Systems and Computing, vol 879. Springer, Cham. https://doi.org/10.1007/978-3-030-02305-8_73
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DOI: https://doi.org/10.1007/978-3-030-02305-8_73
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