Urban Transit Route Network Design Problem using Tabu Search Algorithm

2007 ◽  
Author(s):  
Deming Lei ◽  
Xinping Yan
Keyword(s):  
Tabu Search ◽  
Network Design ◽  
Design Problem ◽  
Search Algorithm ◽  
Network Design Problem ◽  
Tabu Search Algorithm ◽  
Urban Transit ◽  
Route Network ◽  
Transit Route

Tabu Search Algorithm for Survivable Network Design Problem with Simultaneous Unicast and Anycast Flows

2010 ◽  
Vol 56 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Jakub Gładysz ◽  
Krzysztof Walkowiak
Keyword(s):  
Tabu Search ◽  
Network Design ◽  
Design Problem ◽  
Search Algorithm ◽  
Branch And Cut ◽  
Network Design Problem ◽  
Tabu Search Algorithm ◽  
Survivable Network Design ◽  
Network Cost ◽  
Survivable Network

Tabu Search Algorithm for Survivable Network Design Problem with Simultaneous Unicast and Anycast FlowsIn this work we focus on the problem of survivable network design for simultaneous unicast and anycast flows. This problem follows from the growing popularity of network services applying the anycast paradigm. The anycasting is defined as one-to-one-of-many transmission and is applied in Domain Name Service (DNS), peer-to-peer (P2P) systems, Content Delivery Networks (CDN). In this work we formulate two models that enables joint optimization of network capacity, working and backup connections for both unicast and anycast flows. The goal is to minimize the network cost required to protect the network against failures using the single backup path approach. In the first model we consider modular link cost, in the second we are given a set of link proposal and we must select only one of them. Because these problems are NP-hard, therefore optimal solutions of branch-and-bounds or branch-and-cut methods can be generated for relatively small networks. Consequently, we propose a new heuristic algorithm based on Tabu Search method. We present results showing the effectiveness the proposed heuristic compared against optimal results. Moreover, we report results showing that the use of anycast paradigm can reduce the network cost.

scholarly journals A Transit Route Network Design Problem Considering Equity

2019 ◽  
Vol 11 (13) ◽  
pp. 3527 ◽  
Author(s):  
Myeonghyeon Kim ◽  
Seung-Young Kho ◽  
Dong-Kyu Kim
Keyword(s):  
Network Design ◽  
Public Transportation ◽  
Design Problem ◽  
Network Design Problem ◽  
Modal Split ◽  
Route Network ◽  
Line Selection ◽  
Transit Route ◽  
Selection Of

As concerns about environmental quality, social equity, and economic efficiency are increasing, efforts on improving the sustainability of public transportation are being made all over the world. This study aims to propose a transit route network design problem that considers modal and spatial equities. The equities are accommodated by using two indexes that can simultaneously reflect mobility and accessibility. A decision-making process for designing a transit route network consists of the selection of the target line, selection of the target node, the determination of an alternative line, and the implementation of a procedure for setting frequency. The model is configured through bi-level modeling based on an iterative process to calculate the modal split and the traffic and transit assignments with changes in the transit route network. While the frequency of each line is determined by a genetic algorithm in the upper model, the modal split and traffic and transit assignments are implemented in the lower model. This transit route network design model and the associated algorithms are applied to a sample network. As a result, an improved solution with equity and the lower total cost is identified based on a comparison with the existing transit route network.

scholarly journals Some Computational Insights on the Optimal Bus Transit Route Network Design Problem

2012 ◽  
Vol 47 (3) ◽  
Author(s):  
Wei (David) Fan ◽  
Randy B. Machemehl
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Large Scale ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Research Experiences ◽  
Bus Transit ◽  
Route Network ◽  
Transit Route ◽  
Demand Aggregation

The objective of this paper is to present some computational insights based on previous extensive research experiences on the optimal bus transit route network design problem (BTRNDP) with zonal demand aggregation and variable transit demand. A multi-objective, nonlinear mixed integer model is developed. A general meta-heuristics-based solution methodology is proposed. Genetic algorithms (GA), simulated annealing (SA), and a combination of the GA and SA are implemented and compared to solve the BTRNDP. Computational results show that zonal demand aggregation is necessary and combining metaheuristic algorithms to solve the large scale BTRNDP is very promising.

Electric Transit Route Network Design Problem: Model and Application

2019 ◽  
Vol 2673 (8) ◽  
pp. 264-274 ◽  
Author(s):  
Christina Iliopoulou ◽  
Ioannis Tassopoulos ◽  
Konstantinos Kepaptsoglou ◽  
Grigorios Beligiannis
Keyword(s):  
Network Design ◽  
Public Transportation ◽  
Design Problem ◽  
Network Design Problem ◽  
Test Bed ◽  
Problem Model ◽  
Charging Infrastructure ◽  
Route Network ◽  
Proposed Model ◽  
Transit Route

Electric buses have long been recognized as a promising direction for offering sustainable public transportation services. While range and battery performance constraints have hindered the widespread adoption of electric buses in the past, technological advances make them a prominent and attractive option for public transportation in the future. Still, operational constraints and the need for additional (charging) infrastructure highlight the need for introducing appropriate decision-making tools, tailor-made for supporting the design of transit networks operated by electric buses. This paper focuses on developing and testing a comprehensive route design model for the case of a transit network, operated exclusively by an electric bus fleet (Electric Transit Route Network Design Problem—E-TRNDP). The model is formulated as a bi-level optimization problem, which attempts to jointly design efficient transit routes and locate required charging infrastructure. A multi-objective, particle swarm optimization algorithm, coupled with a mixed linear—integer programming model is used to solve the model. An existing benchmark network is used as a test-bed for the proposed model and solution process; results illustrate that the proposed model and solution method yield realistic design outcomes in an acceptable time frame.

Metaheuristics for the transit route network design problem: a review and comparative analysis

2019 ◽  
Vol 11 (3) ◽  
pp. 487-521 ◽  
Author(s):  
Christina Iliopoulou ◽  
Konstantinos Kepaptsoglou ◽  
Eleni Vlahogianni
Keyword(s):  
Comparative Analysis ◽  
Network Design ◽  
Design Problem ◽  
Network Design Problem ◽  
Route Network ◽  
Transit Route
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