A heuristic aided Stochastic Beam Search algorithm for solving the transit network design problem

Abstract Designing efficient routes for a transit network is one of the main problems faced by city planners of the world. Due to the largeness and complexity of modern day road networks it is impossible to make a good route design manually. So, at present computer algorithms are used to design the routes. Designing routes for transit network is a multi-criteria decision making problem which has to search a large solution space to find an optimal solution. This paper presents a novel heuristic that can quickly generate good solutions. Also we propose a Stochastic Beam Search algorithm with a heuristic inspired successor operator. We conduct extensive experiments on some benchmark datasets and perform statistical tests on the results. We show that our algorithm can successfully explore the search space. Also we compare our results with previous studies and show that our algorithms produce superior results. In particular, for large datasets, the solutions generated by our heuristic in less than a second turn out to be better than solutions generated in two hours by the state of the art algorithm.

[1]  Renato Oliveira Arbex,et al.  Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm , 2015 .

[2]  Tapan P. Bagchi,et al.  Multiobjective Scheduling by Genetic Algorithms , 1999 .

[3]  Hani S. Mahmassani,et al.  AN AI-BASED APPROACH FOR TRANSIT ROUTE SYSTEM PLANNING AND DESIGN , 1991 .

[4]  J. Žerovnik Heuristics for NP-hard optimization problems - simpler is better!? , 2015 .

[5]  Douglas L. McWilliams,et al.  A beam search heuristics to solve the parcel hub scheduling problem , 2012, Comput. Ind. Eng..

[6]  Partha Chakroborty,et al.  Genetic Algorithms for Optimal Urban Transit Network Design , 2003 .

[7]  Ihsan Sabuncuoglu,et al.  Job shop scheduling with beam search , 1999, Eur. J. Oper. Res..

[8]  Muhammad Ali Nayeem Solving transit network design problem using evolutionary many-objective approach , 2016 .

[9]  Wei Zheng,et al.  Memory-Enhanced Dynamic Multi-Objective Evolutionary Algorithm Based on Lp Decomposition , 2018, Applied Sciences.

[10]  Christine L. Mumford,et al.  A simple multi-objective optimization algorithm for the urban transit routing problem , 2009, 2009 IEEE Congress on Evolutionary Computation.

[11]  Mhand Hifi,et al.  A beam search algorithm for the circular packing problem , 2009, Comput. Oper. Res..

[12]  P. Chakroborty,et al.  Optimal Route Network Design for Transit Systems Using Genetic Algorithms , 2002 .

[13]  Jairo R. Montoya-Torres,et al.  A beam search heuristic for scheduling a single machine with release dates and sequence dependent setup times to minimize the makespan , 2016, Comput. Oper. Res..

[14]  Milos Nikolic,et al.  A simultaneous transit network design and frequency setting: Computing with bees , 2014, Expert Syst. Appl..

[15]  Débora P. Ronconi,et al.  List scheduling and beam search methods for the flexible job shop scheduling problem with sequencing flexibility , 2015, Eur. J. Oper. Res..

[16]  Andrew Lim,et al.  A stochastic beam search for the berth allocation problem , 2007, Decis. Support Syst..

[17]  Wangtu Xu,et al.  The Memetic algorithm for the optimization of urban transit network , 2015, Expert Syst. Appl..

[18]  Julia A. Bennell,et al.  A beam search approach to solve the convex irregular bin packing problem with guillotine guts , 2018, Eur. J. Oper. Res..

[19]  Christoph E. Mandl,et al.  Evaluation and optimization of urban public transportation networks , 1980 .

[20]  Douglas R. Shier,et al.  On algorithms for finding the k shortest paths in a network , 1979, Networks.

[21]  Mahmoud Owais,et al.  Multi-Objective Transit Route Network Design as Set Covering Problem , 2016, IEEE Transactions on Intelligent Transportation Systems.

[22]  Antonio Mauttone,et al.  A multi-objective metaheuristic approach for the Transit Network Design Problem , 2009, Public Transp..

[23]  Jan Karel Lenstra,et al.  The complexity of the network design problem , 1978, Networks.

[24]  Vincent T'Kindt,et al.  Coupling Genetic Local Search and Recovering Beam Search algorithms for minimizing the total completion time in the single machine scheduling problem subject to release dates , 2012, Comput. Oper. Res..

[25]  Ignacio Araya,et al.  A beam search approach to the container loading problem , 2014, Comput. Oper. Res..

[26]  Pu Wang,et al.  Development of origin–destination matrices using mobile phone call data , 2014 .

[27]  Yuval Hadas,et al.  Urban bus network of priority lanes: A combined multi-objective, multi-criteria and group decision-making approach , 2016 .

[28]  David J. Sheskin,et al.  Handbook of Parametric and Nonparametric Statistical Procedures , 1997 .

[29]  Mahmoud Owais,et al.  Complete hierarchical multi-objective genetic algorithm for transit network design problem , 2018, Expert Syst. Appl..

[30]  Christine L. Mumford,et al.  A metaheuristic approach to the urban transit routing problem , 2010, J. Heuristics.

[31]  W. Lampkin,et al.  The Design of Routes, Service Frequencies, and Schedules for a Municipal Bus Undertaking: A Case Study , 1967 .

[32]  Christian Blum,et al.  On solving the assembly line worker assignment and balancing problem via beam search , 2011, Comput. Oper. Res..

[33]  Avishai Ceder,et al.  Public Transit Planning and Operation: Theory, Modeling and Practice , 2007 .

[34]  Ponnuthurai Nagaratnam Suganthan,et al.  $I_{\rm SDE}$ +—An Indicator for Multi and Many-Objective Optimization , 2019, IEEE Transactions on Evolutionary Computation.

[35]  M. Friedman The Use of Ranks to Avoid the Assumption of Normality Implicit in the Analysis of Variance , 1937 .

[36]  Mahmoud Owais,et al.  Simple and Effective Solution Methodology for Transit Network Design Problem , 2014 .

[37]  Mustafa Gök,et al.  A demand based route generation algorithm for public transit network design , 2014, Comput. Oper. Res..

[38]  Md. Khaledur Rahman,et al.  Transit network design by genetic algorithm with elitism , 2014 .

[39]  Francisco Herrera,et al.  A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms , 2011, Swarm Evol. Comput..

[40]  Milos Nikolic,et al.  Transit network design by Bee Colony Optimization , 2013, Expert Syst. Appl..

[41]  Eric Jones,et al.  SciPy: Open Source Scientific Tools for Python , 2001 .

[42]  M-C Shih,et al.  A DESIGN METHODOLOGY FOR BUS TRANSIT NETWORKS WITH COORDINATED OPERATIONS , 1994 .

[43]  S. Holm A Simple Sequentially Rejective Multiple Test Procedure , 1979 .

[44]  Hani S. Mahmassani,et al.  Hybrid route generation heuristic algorithm for the design of transit networks , 1995 .

[45]  Christine L. Mumford,et al.  New heuristic and evolutionary operators for the multi-objective urban transit routing problem , 2013, 2013 IEEE Congress on Evolutionary Computation.

[46]  Xuesong Zhou,et al.  Single-Track Train Timetabling with Guaranteed Optimality: Branch-and-Bound Algorithms with Enhanced Lower Bounds , 2007 .

[47]  Victor Fernandez-Viagas,et al.  A beam-search-based constructive heuristic for the PFSP to minimise total flowtime , 2017, Comput. Oper. Res..

[48]  W. Y. Szeto,et al.  Hybrid Evolutionary Metaheuristics for Concurrent Multi-Objective Design of Urban Road and Public Transit Networks , 2012 .