Urban Freight Transport: From Optimized Routes to Robust Routes

Guedria, Mohamed; Malhéné, Nicolas; Deschamps, Jean‐Christophe

doi:10.1016/j.trpro.2016.02.076

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…In reference [16], two well-known strategies were implemented in delivery routes in urban areas-the first is the application of the capacitated VRP, and the second is the problem of loading plan optimization. This is based on the use of an approximation with a hybrid method of the two strategies and with the concept of robustness introduced into the route to guarantee a level of predefined service, according to vehicle performance.…”

Section: Literature Reviewmentioning

confidence: 99%

Implementation of a Mathematical Model to Improve Sustainability in the Handling of Transport Costs in a Distribution Network

et al. 2019

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This work considers the application of a mathematical model using mixed-integer linear programming for the vehicle routing problem. The model aims at establishing the distribution routes departing from a distribution center to each customer in order to reduce the transport cost associated with these routes. The study considers the use of a fleet of different capacities in the distribution network, which presents the special characteristic of a star network and which must meet different efficiency criteria, such as the fulfillment of each customer's demand, the vehicle carrying capacity, work schedule, and sustainable use of resources. The intention is to find the amount of equipment suitable to satisfy the demand, thus improving the level of customer service, optimizing the use of both human and economic resources in the distribution area, and leveraging maximum vehicle capacity usage. The MILP mixed-integer linear programming mathematical model of the case study is presented, as well as the corresponding numerical study.

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Section: Literature Reviewmentioning

confidence: 99%

Implementation of a Mathematical Model to Improve Sustainability in the Handling of Transport Costs in a Distribution Network

et al. 2019

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“…In terms of model construction, Goodarzi and Zegordi [2] established a nonlinear mixed-integer programming (MIP) model to optimize the distribution network, consisting of parts suppliers, cross terminals, and assembly factories. Guedria et al [3] optimized the urban vehicle routing and vehicle loading planning. To minimize the total cost of the collaborative multiple centers VRP (CMCVRP), Wang et al [4] designed an integer programming model that considers the effective transport cost in distribution centers (DC) and that of vehicles from each DC, and solved the model with a self-designed multi-phase hybrid algorithm, which combines the merits of clustering, dynamic planning, and heuristic algorithms.…”

Section: Introductionmentioning

confidence: 99%

Collaborative Distribution in the Soft Time Window of Agricultural-Means Supply Chain Based on Simulated Annealing-Genetic Algorithm

Zhu¹,

Wang²,

Li³

2020

JESA

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This paper mainly explores the collaborative distribution to multiple customers at the terminal of agricultural-means supply chain (AMSC). Firstly, a cost optimization model for collaborative distribution constrained by time window was constructed based on fuzzy appointment time function. Next, the proposed model was solved by simulated annealing-genetic algorithm (SA-GA). Through a case study, the cost optimization model constrained by customer satisfaction was compared with that not constrained by customer satisfaction. The results show that the cost optimization model constrained by customer satisfaction made the customers more satisfied without greatly elevating the distribution cost. The research results shed new light on the collaborative distribution of time-sensitive agricultural-means (AM) products, and the management of the AMSC.

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“…After that, many scholars at home and abroad have studied it. Mohamed et al [12] proposed a hybrid model for simultaneous optimization of vehicle routing and loading tasks from the overall process of urban distribution. Patrick et al [13] introduced a new concept of expected delivery interval to balance and quantify the difference of demand between enterprises and users in cost, benefit and distribution reliability.…”

Section: Introductionmentioning

confidence: 99%

“…Suppose N = 10, K = 3, the encoding dimension is (10 + 3 − 1) × 1 = 12 × 1, thus a possible encoding can be (0.12, 0.37, 0.22, 0.96, 0.56, 0.35, 0.76, 0.57, 0.38, 0.91, 0.71, 0.26). Using the random key decoding rule, it is easy to get the integer arrangement (1,5,2,12,7,4,10,8,6,11,9,3). The integers 11 and 12 are the so-called sub-path segmentation, and the vehicle routes are:…”

mentioning

confidence: 99%

Optimizing Urban Distribution Routes for Perishable Foods Considering Carbon Emission Reduction

et al. 2019

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The increasing demand for urban distribution increases the number of transportation vehicles which intensifies the congestion of urban traffic and leads to a lot of carbon emissions. This paper focuses on carbon emission reduction in urban distribution, taking perishable foods as the object. It carries out optimization analysis of urban distribution routes to explore the impact of low carbon policy on urban distribution routes planning. On the basis of analysis of the cost components and corresponding constraints of urban distribution, two optimization models of urban distribution routes with and without carbon emissions cost are constructed. Fuel quantity related to cost and carbon emissions in the model is calculated based on traffic speed, vehicle fuel quantity and passable time period of distribution. Then an improved algorithm which combines genetic algorithm and tabu search algorithm is designed to solve models. Moreover, an analysis of the influence of carbon tax price is also carried out. It is concluded that in the process of urban distribution based on the actual network information, path optimization considering the low carbon factor can effectively reduce the distribution process of CO 2 , and reduce the total cost of the enterprise and society, thus achieving greater social benefits at a lower cost. In addition, the government can encourage low-carbon distribution by rationally adjusting the price of carbon tax to achieve a higher social benefit.

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Urban Freight Transport: From Optimized Routes to Robust Routes

Cited by 7 publications

References 8 publications

Implementation of a Mathematical Model to Improve Sustainability in the Handling of Transport Costs in a Distribution Network

Implementation of a Mathematical Model to Improve Sustainability in the Handling of Transport Costs in a Distribution Network

Collaborative Distribution in the Soft Time Window of Agricultural-Means Supply Chain Based on Simulated Annealing-Genetic Algorithm

Optimizing Urban Distribution Routes for Perishable Foods Considering Carbon Emission Reduction

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