Resource Assignment Problem for Fleet Management Considering Outsourcing: Modelling and a Decomposition Approach

2021 ◽  
pp. 260-273
Author(s):  
Filipe Monnerat ◽  
Joana Dias ◽  
Maria João Alves
Keyword(s):  
Assignment Problem ◽  
Fleet Management ◽  
Resource Assignment ◽  
Decomposition Approach

A resource assignment problem on graphs

1995 ◽  
pp. 418-427 ◽  
Author(s):  
Satoshi Fujita ◽  
Tiko Kameda ◽  
Masafumi Yamashita
Keyword(s):  
Assignment Problem ◽  
Resource Assignment

A Logic-Based Benders Decomposition Approach for the VNF Assignment Problem

2019 ◽  
Vol 7 (4) ◽  
pp. 894-906 ◽  
Author(s):  
Sara Ayoubi ◽  
Samir Sebbah ◽  
Chadi Assi
Keyword(s):  
Assignment Problem ◽  
Benders Decomposition ◽  
Decomposition Approach

scholarly journals A decomposition approach to the static traffic assignment problem

2017 ◽  
Vol 105 ◽  
pp. 270-296 ◽  
Author(s):  
Ehsan Jafari ◽  
Venktesh Pandey ◽  
Stephen D. Boyles
Keyword(s):  
Assignment Problem ◽  
Traffic Assignment ◽  
Decomposition Approach ◽  
Traffic Assignment Problem

Network Partitioning Algorithms for Solving the Traffic Assignment Problem using a Decomposition Approach

2018 ◽  
Vol 2672 (48) ◽  
pp. 116-126 ◽  
Author(s):  
Cesar N. Yahia ◽  
Venktesh Pandey ◽  
Stephen D. Boyles
Keyword(s):  
Assignment Problem ◽  
Traffic Assignment ◽  
Computation Time ◽  
Graph Laplacian ◽  
Lower Number ◽  
Network Partitioning ◽  
Agglomerative Clustering ◽  
Decomposition Approach ◽  
Traffic Assignment Problem ◽  
Spectral Partitioning

Recent methods in the literature to parallelize the traffic assignment problem consider partitioning a network into subnetworks to reduce the computation time. In this article, a partitioning method is sought that generates subnetworks minimizing the computation time of a decomposition approach for solving the traffic assignment (DSTAP). The aim is to minimize the number of boundary nodes, the interflow between subnetworks, and the computation time when the traffic assignment problem is solved in parallel on the subnetworks. Two different methods for partitioning are tested. The first is an agglomerative clustering heuristic that reduces the subnetwork boundary nodes. The second is a flow weighted spectral partitioning algorithm that uses the normalized graph Laplacian to partition the network. The performance of both algorithms is assessed on different test networks. The results indicate that the agglomerative heuristic generates subnetworks with a lower number of boundary nodes, which reduces the per iteration computation time of DSTAP. However, the partitions generated may be heavily imbalanced leading to a higher computation time when the subnetworks are solved in parallel separately at a particular DSTAP iteration. For the Austin network partitioned into four subnetworks, the agglomerative heuristic requires 3.5 times more computation time to solve the subnetworks in parallel. The results also show that the spectral partitioning method is superior for minimizing the interflow between subnetworks. This leads to a faster convergence rate of the DSTAP algorithm.

A Benders Decomposition Approach for the Locomotive and Car Assignment Problem

2000 ◽  
Vol 34 (2) ◽  
pp. 133-149 ◽  
Author(s):  
Jean-François Cordeau ◽  
François Soumis ◽  
Jacques Desrosiers
Keyword(s):  
Assignment Problem ◽  
Benders Decomposition ◽  
Decomposition Approach

A Study on r-Configurations---A Resource Assignment Problem on Graphs

2000 ◽  
Vol 13 (2) ◽  
pp. 227-254 ◽  
Author(s):  
Satoshi Fujita ◽  
Masafumi Yamashita ◽  
Tiko Kameda
Keyword(s):  
Assignment Problem ◽  
Resource Assignment

scholarly journals Developing Vehicle Locations Strategy on Urban Road

2017 ◽  
Vol 18 (4) ◽  
pp. 253-262 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Assignment Problem ◽  
Urban Areas ◽  
Road Traffic ◽  
Cellular Systems ◽  
Traffic Data ◽  
Resource Assignment ◽  
Urban Road ◽  
Road Congestion ◽  
Different Sources ◽  
Limited Coverage

Abstract Various forecasting schemes have been proposed to manage urban road traffic data, which is collected by different sources such as, videos cameras, sensors and mobile phone services. However, these are not sufficient for the purpose because of their limited coverage and high costs of installation and maintenance. This paper describes urban road congestion as a resource assignment problem in urban areas, in which vehicles are assigned to available sections of road. In order to accomplish this and reduce road congestion, an estimation of the vehicle location is needed. Different strategies for estimating location have been proposed, such as the use of Wi-Fi and cellular systems, and GPS/GNSS. In this process, accuracy plays an important role. Therefore, to increase the accuracy of the primary GNSS system, an augmentation system is considered.

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