Sustainable Facility Location-Routing Problem for Blood Package Delivery by Drones with a Charging Station

2021 ◽  
pp. 3-14
Author(s):  
Shirin Ghasemi ◽  
Reza Tavakkoli-Moghaddam ◽  
Mahdi Hamid ◽  
Meysam Hosseinzadeh
Keyword(s):  
Facility Location ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Charging Station ◽  
Location Routing ◽  
Package Delivery

A Two-Phase Meta Heuristic Approach to the Location-Routing Problem for Transportation Network Planning

2013 ◽  
Vol 361-363 ◽  
pp. 1900-1905 ◽  
Author(s):  
Ji Ung Sun
Keyword(s):  
Ant Colony Optimization ◽  
Facility Location ◽  
Vehicle Routing ◽  
Optimization Algorithm ◽  
Transportation Network ◽  
Ant Colony Optimization Algorithm ◽  
Two Phase ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

In this paper we consider the location-routing problem which combines the facility location and the vehicle routing decisions. In this type of problem, we have to determine the location of facilities within a set of possible locations and routes of the vehicles to meet the demands of number of customers. Since the location-routing problem is NP-hard, it is difficult to obtain optimal solution within a reasonable computational time. Therefore, a two-phase ant colony optimization algorithm is developed which solves facility location problem and vehicle routing problem hierarchically. Its performance is examined through a comparative study. The experimental results show that the proposed ant colony optimization algorithm can be a viable solution method for the general transportation network planning.

scholarly journals Application of Hierarchical Facility Location-Routing Problem with Optimization of an Underground Logistic System: A Case Study in China

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Yingpeng Hu ◽  
Kaixi Zhang ◽  
Jing Yang ◽  
Yanghui Wu
Keyword(s):  
Facility Location ◽  
Facility Location Problem ◽  
Construction Cost ◽  
Transport Cost ◽  
Location Routing Problem ◽  
Logistics System ◽  
Routing Problem ◽  
Location Routing ◽  
Collection Sites

Facility location problem (FLP) and vehicle routing problem (VRP) are two of the most challenging issues in logistics. This paper presents an exploration of the multinode facility location-routing problem with realistic conditions. The disposal centers, transfer stations, connected collection sites, and unconnected collection sites are built into a new hierarchical model which is solved by Generate Algorithm (GA). Model costs include node construction cost, pipeline construction cost, transport cost, and transfer cost. This paper considers that the transportation is a bidirectional flow not a single flow; each pairs node in the area needs transportation; the dynamic routing selection method is used to determine the routes of unconnected collection sites. FLP and VRP can be both solved in this model. To illustrate the applicability of the model, a case study is presented and the results are discussed. The model in this paper can reduce the cost of the traditional underground logistics system by 6%~8% in experiments.

An Effective Variable Neighborhood Search with Perturbation for Location-Routing Problem

2019 ◽  
Vol 28 (07) ◽  
pp. 1950024
Author(s):  
Hua Jiang ◽  
Corinne Lucet ◽  
Laure Devendeville ◽  
Chu-Min Li
Keyword(s):  
Facility Location ◽  
Vehicle Routing ◽  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Challenging Problem ◽  
Waste Collection ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Practical Applications ◽  
Location Routing

Location-Routing Problem (LRP) is a challenging problem in logistics, which combines two types of decision: facility location and vehicle routing. In this paper, we focus on LRP with multiple capacitated depots and one uncapacitated vehicle per depot, which has practical applications such as mail delivery and waste collection. We propose a simple iterated variable neighborhood search with an effective perturbation strategy to solve the LRP variant. The experiments show that the algorithm is efficient and can compute better solutions than previous algorithms on tested instances.

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