Public Transport Route Finding using a Hybrid Genetic Algorithm

In this paper we present a public transport route finding solution based on a hybrid genetic algorithm. The algorithm uses two heuristics that take into consideration the number of trans-fers and the remaining distance to the destination station in order to improve the convergence speed. The interface of the system uses the latest web technologies to offer both portability and advanced functionality. The approach has been evaluated using the data for the Bucharest public transport network.Route Finding, Evolutionary Algorithms, Hybrid Genetic Algorithm

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

The design of public transit networks with heuristic algorithms : case study Cape Town

Includes bibliographical references.The Transit Network Design Problem (TNDP) is well-researched in the field of transportation planning. It deals with the design of optimized public transportation networks and systems, and belongs to the class of non-linear optimization problems. In solving the problem, attempts are made to balance the tradeoffs between utility maximization and cost minimization given some resource constraints, within the context of a transportation network. In this dissertation, the design of a public transit network is undertaken and tested for Cape Town. The focus of the research is on obtaining an optimal network configuration that minimizes cost for both users and operators of the network. In doing so, heuristic solution algorithms are implemented in the design process, since they are known to generate better results for non-linear optimization problems than analytical ones. This algorithm which is named a Bus Route Network Design Algorithm (BRNDA) is based on genetic algorithms. Furthermore, it has three key components namely: 1) Bus Route Network Generation Algorithm (BRNGA) - which generates the potential network solutions; 2) Bus Route Network Analysis Procedure (BRNAP) - which evaluates the generated solutions; 3) Bus Route Network Search Algorithm (BRNSA) - which searches for an optimal or near optimal network option, among the feasible ones. The solution approach is tested first on a small scale network to demonstrate its numerical results, then it is applied to a large scale network, namely the Cape Town road network

Does First Last: The Existence and Extent of First Mover Advantages on Spatial Networks

This paper examines the nature of first mover advantages on spatially-differentiated surface transportation networks. The literature on first mover advantages identifies a number of sources that explain their existence. However whether those sources exist on spatial networks, and how they play out with true capital immobility have been unanswered questions. By examining empirical examples including commuter rail and the Underground in London and roads in the Twin Cities of Minneapolis and St. Paul, first mover advantages were observed in rail stations but not in the road network. A simulation model was then constructed to replicate the growth of surface transportation networks incorporating idealized deployment decisions and to test whether the first network elements (links, nodes) remain strongest (or even strong) into the future. Simulation experiments were conducted and Spearman rank correlation tests revealed that first mover advantages exist in both nodes and links and become increasingly prominent as the network evolves due to the accumulated advantage of earlier established network elements. Simulation results also disclosed that network growth with a higher concentration of initial land uses results in stronger first mover advantages, and that the extent may vary as the topological attributes of the network change over time. The sensitivity of simulation results on model parameters are also discussed.First mover advantage, transport, land use, London Underground, London railways, network growth, induced demand, induced supply

Mobility study based on the analysis of Bluetooth data in the city of Brisbane

In the field of transport planning, many studies have examined the effectiveness of different algorithms related to the problem of transport network design. However, no study has considered the alternative of a problem of transport network modification, which consists of making small alterations to the current network without having to entirely design it. The focus of this research is on designing an algorithm able to find the optimal route for placing a new public transport line, understanding optimal as capable of minimizing the traffic of private vehicles around the city. As observed, it corresponds to one case of transport network modification. Data used in this project were collected by the detection of devices through the Bluetooth sensors spread over the city of Brisbane, Australia. The use of real data led to the need of a previous analysis and cleaning of the database, in order to obtain results which are feasible and reliable. Since it is a non-linear optimization problem, heuristic solution algorithms are used in the design procedure. The algorithm proposed is based on genetic algorithms, and it has been adjusted to this case of study by adapting the functions that compound the algorithm. The proposed model was tested and the results obtained analysed, concluding that the designed algorithm is effective for generating routes able to minimize the car flow in a transport network

Mobility study based on the analysis of Bluetooth data in the city of Brisbane

In the field of transport planning, many studies have examined the effectiveness of different algorithms related to the problem of transport network design. However, no study has considered the alternative of a problem of transport network modification, which consists of making small alterations to the current network without having to entirely design it. The focus of this research is on designing an algorithm able to find the optimal route for placing a new public transport line, understanding optimal as capable of minimizing the traffic of private vehicles around the city. As observed, it corresponds to one case of transport network modification. Data used in this project were collected by the detection of devices through the Bluetooth sensors spread over the city of Brisbane, Australia. The use of real data led to the need of a previous analysis and cleaning of the database, in order to obtain results which are feasible and reliable. Since it is a non-linear optimization problem, heuristic solution algorithms are used in the design procedure. The algorithm proposed is based on genetic algorithms, and it has been adjusted to this case of study by adapting the functions that compound the algorithm. The proposed model was tested and the results obtained analysed, concluding that the designed algorithm is effective for generating routes able to minimize the car flow in a transport network