Sürdürülebilir Şehir İçi Dinamik Araç Rotalama Problemi Üzerine Bir Karar Destek Sistemi Önerisi
Özet
The logistics industry is modified by legal regulations and restrictions introduced within the context of sustainability. These regulations are taken to reduce all negative factors such as greenhouse gas emission problems related to vehicle use, harmful effects of these gases on human health, an increase in noise level and traffic accidents. In this study, it is aimed to develop a decision support system that can be used within the scope of sustainable logistics management for dynamic urban distribution problems. To achieve this aim, in the first part of this study, the main logistic objectives and performance indicators in the sustainable urban vehicle routing problem and the decision support models in the literature were analyzed. According to the results of the literature review, it has been observed that in studies taking the green or sustainability indicators into account, logistics costs might be reduced significantly in addition to the decrease in greenhouse gas emissions. Also, it was found that the realistic slope of the roads was not considered in the fuel consumption functions employed. In the light of this finding, in the second part of the study, the effects of considering explicit fuel consumption calculation and dynamic customer demand on the performance indicators of the traveling salesman problem were investigated. Realistic road slopes were obtained from the geographic information system and actual distances, and speeds were obtained from Google maps, to calculate an explicit fuel consumption. In order to determine how much benefit was achieved in the routes created by calculating explicit fuel consumption, numerical analysis of the routes created with distance minimization, travel time minimization, fuel minimization by assuming the road slope as zero, fuel minimization by assuming the slope as average, and fuel minimization by assuming the slope as realistic, was made. The decision support system developed for the collection of laboratory samples from 42 family health clinics, in central districts of Ankara, can handle the dynamic requests. It can optimize the routes by taking into account the demand updates (demand addition-subtraction) occurring after the start of delivery operations. According to the results obtained, the calculation of fuel consumption by taking the realistic road slopes into account provides fuel savings of up to 1.15% in static scenarios and 34.15% in dynamic scenarios. It is seen that this study will contribute to the literature in terms of guiding future studies on urban sustainable vehicle routing problem and fuel consumption calculation method.
