How to anticipate the level of activity of a sustainable collaborative network: the case of urban freight delivery through logistics platforms

International audienceIn this paper, we elaborate a methodology to study a particular case of collaborative network: city logistics. We identify that many solutions for urban logistics are, most of time, badly evaluated. Indeed, the theory often predicts a positive effect but the reality is most of time counterbalanced. We tried to fill this gap by making use of innovative methods. To do so, we mobilize several domains of knowledge: operational research, game theory and transportation studies on real cases. We suggest a solution to anticipate the level of activity of an Urban Consolidation Center and determine the condition under which it generates benefit for a carrier using or not, the collaborative network. We present the result obtained by application of our method on the real case of the city of Saint-Etienne

Modelación En Programación Matemática Y Resolución Del Problema De Localización-Ruteo En Logística Urbana

The implementation of urban distribution centers near to city centers to allow freight consolidation is a widely extended initiative worldwide, seeking to improve traffic congestion and quality of life in downtown, among others. This paper considers the problem of locating urban distribution centers and proposes an exact method, based on integer linear programming for strategic, tactical and operational decision-making. The aim is to solve, in an integer manner, location, sizing and operation (vehicle routing) problems in these logistics platforms. The model is validated using real-data taken from the city of SaintÉtienne, France. Computational experiments are also carried out in order to compare the proposed model with existing procedures from the literature. Results show the efficiency and effectiveness of the proposed model and its applicability in real decision-making for medium sized data sets

Modelación En Programación Matemática Y Resolución Del Problema De Localización-Ruteo En Logística Urbana

The implementation of urban distribution centers near to city centers to allow freight consolidation is a widely extended initiative worldwide, seeking to improve traffic congestion and quality of life in downtown, among others. This paper considers the problem of locating urban distribution centers and proposes an exact method, based on integer linear programming for strategic, tactical and operational decision-making. The aim is to solve, in an integer manner, location, sizing and operation (vehicle routing) problems in these logistics platforms. The model is validated using real-data taken from the city of SaintÉtienne, France. Computational experiments are also carried out in order to compare the proposed model with existing procedures from the literature. Results show the efficiency and effectiveness of the proposed model and its applicability in real decision-making for medium sized data sets

Short- and mid-term evaluation of the use of electric vehicles in urban freight transport collaborative networks: a case study

Despite its negative impacts, freight transportation is a primary component of all supply chains. Decision makers have considered diverse strategies, such as Horizontal Collaboration (HC) and the usage of alternative types of vehicles, to reduce overall cost and the related environmental and social impacts. This paper assesses the implementation of an electric fleet of vehicles in urban goods distribution under HC strategy between carriers. A biased randomisation based algorithm is used to solve the problem with a multi-objective function to explore the relationships between both delivery and environmental costs. Real data from the city of Bogota, Colombia are used to validate this approach. Experiments with different costs and demands projections are performed to analyse short- and medium-term impacts related to the usage of electric vehicles in collaborative networks. Results show that the optimal selection of vehicle types depends considerably on the time horizon evaluation and demand variation.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT) and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the Special Patrimonial Fund from Universidad de La Sabana (Colombia) and the doctoral grant from the UOC-Open University of Catalonia (Spain)

Solución de los problemas de localización y dimensionamiento de centros urbanos de distribución y enrutamiento de sus vehículos

50 páginasEn la mayoría de las grandes y medianas ciudades, las operaciones de transporte de mercancías tienen un impacto notable en la movilidad del tráfico urbano, así como en las actividades comerciales de la ciudad. La creación de centros urbanos de distribución cerca del centro de las ciudades para consolidar las cargas, es una iniciativa implementada alrededor del mundo que busca disminuir la congestión del tráfico vehicular en las calles y la calidad de vida sus habitantes. Este trabajo considera el problema de localizar los centros de distribución en las zonas urbanas y propone un enfoque para la toma de decisiones a nivel estratégico, táctico y operativo. Se busca resolver, de manera integral, los problemas de localización, dimensionamiento y operación (ruteo de camiones) en estas terminales logísticas. El enfoque es validado usando datos de la vida real provenientes de la ciudad de SaintÉtienne, Francia. Así mismo, se realizan comparaciones experimentales con procedimientos existentes en la literatura. Los resultados muestran la eficiencia y efectividad del enfoque propuesto y su aplicabilidad en la realidad, para instancias hasta de tamaño grande donde, las salidas del enfoque, deben ser analizadas por el tomador de decisiones y pueden mejorar la competitividad del sistema logístico y las condiciones ambientales y sociales de la ciudad en cuestión

Pemodelan Logistik Perkotaan Kota Surabaya Untuk Komoditas Bahan Pangan Pokok Dengan Mempertimbangkan Distribution Center

Pertumbuhan penduduk dan meningkatnya urbanisasi menyebabkan peningkatan kepadatan di kawasan kota. Peningkatan ini berdampak pada meningkatnya kebutuhan bahan pangan pokok. Sebagai kota metropolitan, pasokan bahan panan pokok berasal dari luar kota dan terjadi setiap harinya, terutama pada pasar-pasar tradisional. Adanya distribution center (DC) dapat memberikan pengelolaan yang baik terhadap logistik perkotaan dan dikelola oleh Pemerintah Kota Surabaya. Aktivitas logistik yang terjadi dapat diukur sehingga diketahui dampaknya terhadap kota. Pengukuran kinerja atau performansi aktivitas logistik dapat diukur berdasarkan model logistik. Penelitian ini dilakukan untuk membuat model logistik pada komoditas bahan pangan pokok dengan kondisi nyata (tanpa DC) dan dengan adanya DS sehingga dapat dilakukan pengukuran terhadap performansinya. Pemilihan rute pada kondisi nyata dilakukan dengan algirtma Dijkstra sehingga diperoleh rute tertentu. Rute ini juga merupakan rute yang dapat dilalui pada jaringan jalan dalam kota. Sedangkan untuk rute pengiriman dari DC menuju pasar dikategirikan ke dalam masalah split delivery vehicle routing problem with time windows sehingga dapat dilakukan pengelolaan pengiriman yang terkendali oleh satu kebijakan yang ditetapkan oleh pemerintah. Selain pengukuran, penelitian ini juga memberikan beberapa pilihan skenario terkait pendirian DC. Model, pengukuran, dan alternatif pemilihan lokasi DC diakomodasi dengan pendekatan perancangan aplikasi menggunakan Visual Basic for Application pada Microsoft Excel. ================================================================================================ Population growth and increasing urbanization have caused increased density in the city area. This increase has an impact on the increase in basic food needs. As a metropolitan city, the supply of basic ingredients comes from outside the city and occurs every day, especially in traditional markets. The distribution center (DC) can provide good management of urban logistics and is managed by the Surabaya City Government. Logistical activities that occur can be measured so that the impact on the city is known. The measurement of logistics activity performance can be measured based on the logistic model. This research was conducted to make a logistic model on staple food commodities with real conditions (without DC) and with the presence of DS so that measurements can be made on their performance. Route selection in real conditions is done by Dijkstra's algorithm so that certain routes are obtained. This route is also a route that can be traversed on the road network in the city. Whereas the shipping route from DC to the market is categorized as a problem with split delivery vehicle routing problems with time windows so that management of controlled delivery can be carried out by a policy determined by the government. In addition to measurement, this study also provides several choices of scenarios related to the establishment of DC. Models, measurements, and alternatives for selecting DC locations are accommodated by an application approach using Visual Basic for Application in Microsoft Excel

A simulation-based algorithm for the integrated location and routing problem in urban logistics

In most medium and large sized cities around the world, freight transportation operations might have a noticeable impact on urban traffic mobility as well as on city commercial activities. In order to reduce both traffic congestion and pollution levels, several initiatives have been traditionally implemented. One of the most common strategies concerns the allocation of urban distribution warehouses near the city center in order to consolidate freight delivery services. This paper considers the integrated problem of locating distribution centers in urban areas and the corresponding freight distribution (vehicle routing). The combined problem is solved by using a hybrid algorithm which employs Monte Carlo simulation to induce biased randomness into several stages of the optimization procedure. The approach is then validated using real-life data and comparing our results with results from other works already available in the existing literature

A simulation-based algorithm for the integrated location and routing problem in urban logistics

In most medium and large sized cities around the world, freight transportation operations might have a noticeable impact on urban traffic mobility as well as on city commercial activities. In order to reduce both traffic congestion and pollution levels, several initiatives have been traditionally implemented. One of the most common strategies concerns the allocation of urban distribution warehouses near the city center in order to consolidate freight delivery services. This paper considers the integrated problem of locating distribution centers in urban areas and the corresponding freight distribution (vehicle routing). The combined problem is solved by using a hybrid algorithm which employs Monte Carlo simulation to induce biased randomness into several stages of the optimization procedure. The approach is then validated using real-life data and comparing our results with results from other works already available in the existing literature

A simulation-based algorithm for the integrated location and routing problem in urban logistics

In most medium and large sized cities around the world, freight transportation operations might have a noticeable impact on urban traffic mobility as well as on city commercial activities. In order to reduce both traffic congestion and pollution levels, several initiatives have been traditionally implemented. One of the most common strategies concerns the allocation of urban distribution warehouses near the city center in order to consolidate freight delivery services. This paper considers the integrated problem of locating distribution centers in urban areas and the corresponding freight distribution (vehicle routing). The combined problem is solved by using a hybrid algorithm which employs Monte Carlo simulation to induce biased randomness into several stages of the optimization procedure. The approach is then validated using real-life data and comparing our results with results from other works already available in the existing literature