A novel structure to model the distribution of relief items in a post-disaster situation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Sakiani ◽  
Abbas Seifi ◽  
Reza Ramezani Khorshiddost
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Network Flow ◽  
Routing Problem ◽  
Content Type ◽  
Realistic Case ◽  
Novel Structure ◽  
Disaster Situation ◽  
Post Disaster

Purpose There is usually a considerable shortage of resources and a lack of accurate data about the demand amount in a post-disaster situation. This paper aims to model the distribution and redistribution of relief items. When the new data on demand and resources become available the redistribution of previously delivered items may be necessary due to severe shortages in some locations and surplus inventory in other areas. Design/methodology/approach The presented model includes a vehicle routing problem in the first period and some network flow structures for succeeding periods of each run. Thereby, it can produce itineraries and loading plans for each vehicle in all periods when it is run in a rolling horizon manner. The fairness in distribution is sought by minimizing the maximum shortage of commodities among the affected areas while considering operational costs. Besides, equity of welfare in different periods is taken into account. Findings The proposed model is evaluated by a realistic case study. The results show that redistribution and multi-period planning can improve efficiency and fairness in supply after the occurrence of a disaster. Originality/value This paper proposes an operational model for distribution and redistribution of relief items considering the differences of items characteristics. The model integrates two well-known structures, vehicle routing problem with pickup and delivery and network flow problem to take their advantages. To get more practical results, the model relaxes some simplifying assumptions commonly used in disaster relief studies. Furthermore, the model is used in a realistic case study.

scholarly journals Capacitated vehicle routing problem model for carriers

2018 ◽  
Vol 12 ◽  
Author(s):  
Irma-Delia Rojas-Cuevas ◽  
Santiago-Omar Caballero-Morales ◽  
Jose-Luis Martinez-Flores ◽  
Jose-Rafael Mendoza-Vazquez
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Network Flow ◽  
Route Planning ◽  
Test Problems ◽  
Optimal Route ◽  
Routing Problem ◽  
Problem Model ◽  
Capacitated Vehicle Routing Problem ◽  
Capacitated Vehicle

Background: The Capacitated Vehicle Routing Problem (CVRP) is one of the most important transportation problems in logistics and supply chain management. The standard CVRP considers a fleet of vehicles with homogeneous capacity that depart from a warehouse, collect products from (or deliver products to) a set of customer locations (points) and return to the same warehouse. However, the operation of carrier companies and third-party transportation providers may follow a different network flow for collection and delivery. This may lead to non-optimal route planning through the use of the standard CVRP.Objective: To propose a model for carrier companies to obtain optimal route planning.Method: A Capacitated Vehicle Routing Problem for Carriers (CVRPfC) model is used to consider the distribution scenario where a fleet of vehicles depart from a vehicle storage depot, collect products from a set of customer points and deliver them to a specific warehouse before returning to the vehicle storage depot. Validation of the model’s functionality was performed with adapted CVRP test problems from the Vehicle Routing Problem LIBrary. Following this, an assessment of the model’s economic impact was performed and validated with data from a real carrier (real instance) with the previously described distribution scenario.Results: The route planning obtained through the CVRPfC model accurately described the network flow of the real instance and significantly reduced its distribution costs.Conclusion: The CVRPfC model can thus improve the competitiveness of the carriers by providing better fares to their customers, reducing their distribution costs in the process.

scholarly journals Methodology to Solve the Combination of the Generalized Assignment Problem and the Vehicle Routing Problem: A Case Study in Drug and Medical Instrument Sales and Service

2018 ◽  
Vol 9 (1) ◽  
pp. 3 ◽  
Author(s):  
Malichan Thongkham ◽  
Sasitorn Kaewman
Keyword(s):  
Local Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Routing Problem ◽  
Search Techniques ◽  
De Algorithm ◽  
Local Searches ◽  
Generalized Assignment ◽  
Linear Probability

This article presents algorithms for solving a special case of the vehicle routing problem (VRP). We define our proposed problem of a special VRP case as a combination of two hard problems: the generalized assignment and the vehicle routing problem. The different evolution (DE) algorithm is used to solve the problem. The recombination process of the original DE is modified by adding two more sets of vectors—best vector and random vector—and using two other sets—target vector and trial vector. The linear probability formula is proposed to potentially use one out of the four sets of vectors. This is called the modified DE (MDE) algorithm. Two local searches are integrated into the MDE algorithm: exchange and insert. These procedures create a DE and MDE that use (1) no local search techniques, (2) two local search techniques, (3) only the exchange procedure, and (4) only the insert procedure. This generates four DE algorithms and four MDE algorithms. The proposed methods are tested with 15 tested instances and one case study. The current procedure is compared with all proposed heuristics. The computational result shows that, in the case study, the best DE algorithm (DE-4) has a 1.6% better solution than that of the current practice, whereas the MDE algorithm is 8.2% better. The MDE algorithm that uses the same local search as the DE algorithms generates a maximum 5.814% better solution than that of the DE algorithms.

Optimization of the simultaneous pickup and delivery vehicle routing problem based on carbon tax

2019 ◽  
Vol 119 (9) ◽  
pp. 2055-2071 ◽  
Author(s):  
Gaoyuan Qin ◽  
Fengming Tao ◽  
Lixia Li ◽  
Zhenyu Chen
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Carbon Tax ◽  
Pickup And Delivery ◽  
Vehicle Speed ◽  
Low Carbon ◽  
Delivery Vehicle ◽  
Routing Problem ◽  
Content Type ◽  
Simultaneous Pickup And Delivery

Purpose In order to reduce logistics transportation costs and respond to low-carbon economy, the purpose of this paper is to study the more practical and common simultaneous pickup and delivery vehicle routing problem, which considers the carbon tax policy. A low-carbon simultaneous pickup and delivery vehicle routing problem model is constructed with the minimum total costs as the objective function. Design/methodology/approach This study develops a mathematical optimization model with the minimum total costs, including the carbon emissions costs as the objective function. An adaptive genetic hill-climbing algorithm is designed to solve the model. Findings First, the effectiveness of the algorithm is verified by numerical experiments. Second, the research results prove that carbon tax mechanism can effectively reduce carbon emissions within effective carbon tax interval. Finally, the research results also show that, under the carbon tax mechanism, the effect of vehicle speed on total costs will become more obvious with the increase of carbon tax. Research limitations/implications This paper only considers the weight of the cargo, but it does not consider the volume of the cargo. Originality/value Few studies focus on environmental issues in the simultaneous pickup and delivery problem. Thus, this paper constructs a green path optimization model, combining the carbon tax mechanism for the problem. This paper further analyzes the impact of carbon tax value on total costs and carbon emission; at the same time, the effect of vehicle speed on total cost is also analyzed.

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