Transit Route Network Design Using Frequency Coded Genetic Algorithm

Tom, V. M.; Mohan, S.

doi:10.1061/(asce)0733-947x(2003)129:2(186)

Cited by 151 publications

(94 citation statements)

References 13 publications

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“…Fan et al (2006) use Simulated Annealing to solve a transit network design problem. Ngamchai and Lovell (2003) and Tom and Mohan (2003) use Genetic Algorithms to solve the same type of problems.…”

Section: State Of the Artmentioning

confidence: 99%

Improved rapid transit network design model: considering transfer effects

Cadarso

Marı́n

2015

Ann Oper Res

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The rail rapid transit network design problem aims at locating train alignments and stations, maximizing demand coverage while competing with the current existing networks. We present a model formulation for computing tight bounds of the linear relaxation of the problem where transfers are also introduced. The number of transfers within a trip is a decisive attribute for attracting passengers: transferring is annoying and undesirable for passengers. We conduct computational experiments on different networks and show how we are able to solve more efficiently problems that have been already solved; sensitivity analysis on several model parameters are also performed so as to demonstrate the robustness of the new formulation.

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Section: State Of the Artmentioning

confidence: 99%

Improved rapid transit network design model: considering transfer effects

Cadarso

Marı́n

2015

Ann Oper Res

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“…Genetic algorithms (GAs), which are robust optimization techniques, have been used successfully for routing and scheduling problems. Pattnaik et al (998), Gundaliya et al (2000), and Tom and Mohan (2003) used GAs for the design of bus route networks. Shrivastava and Dhingra (2002) successfully generated coordinated schedules of public buses for existing schedules of suburban trains on the developed feeder route network using GAs.…”

Section: Literature Review and Objective Of Studymentioning

confidence: 99%

Design of Feeder Route Network Using Combined Genetic Algorithm and Specialized Repair Heuristic

Shrivastava¹,

O’Mahony

2007

JPT

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“…They first generated network alternatives and then determined the best alternative using a genetic algorithm. Tom and Mohan [10] extended this algorithm by including new variables and coding schemes. Bielli et al [11] designed a genetic algorithm to optimize a bus network with the objective of increasing the efficiency of the original network and reducing the number of bus vehicles used without increasing passengers' travel times.…”

Section: Introduction 11 Backgroundmentioning

confidence: 99%

Optimization of Trip-end Networks and Ride Price for Express Coach Systems in the High-speed Rail Era

Yang

Jiannan

2017

PROMET

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Express coach (EC) lost a considerable share of passengers after high-speed rail (HSR) was implemented. This paper proposes a door-to-door operation mode for the EC system and builds a model to design an EC trip-end network in the origin city with the aim of maximizing the EC's daily operating profit. A case study is undertaken, and the results show that the operating profit of the EC system first increases and then decreases with the growth of the trip-end routes.In the HSR era, door-to-door operation can effectively guarantee the market share and operating profits of the EC.

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Transit Route Network Design Using Frequency Coded Genetic Algorithm

Cited by 151 publications

References 13 publications

Improved rapid transit network design model: considering transfer effects

Improved rapid transit network design model: considering transfer effects

Design of Feeder Route Network Using Combined Genetic Algorithm and Specialized Repair Heuristic

Optimization of Trip-end Networks and Ride Price for Express Coach Systems in the High-speed Rail Era

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