Capítols de llibre
http://hdl.handle.net/2117/3630
2017-01-19T15:15:20ZDynamic OD transit matrix estimation: formulation and model-building environment
http://hdl.handle.net/2117/27608
Dynamic OD transit matrix estimation: formulation and model-building environment
Montero Mercadé, Lídia; Codina Sancho, Esteve; Barceló Bugeda, Jaime
The aim of this paper is to provide a detailed description of a framework for the estimation of time-sliced origin-destination (OD) trip matrices in a transit network using counts and travel time data of Bluetooth Smartphone devices carried by passengers at equipped transit-stops. A Kalman filtering formulation defined by the authors has been included in the application. The definition of the input for building the space-state model is linked to network scenarios modeled with the transportation planning platform EMME. The transit assignment framework is optimal strategy-based, which determines the subset of paths related to the optimal strategies between all OD pairs
2015-04-27T18:38:07ZMontero Mercadé, LídiaCodina Sancho, EsteveBarceló Bugeda, JaimeThe aim of this paper is to provide a detailed description of a framework for the estimation of time-sliced origin-destination (OD) trip matrices in a transit network using counts and travel time data of Bluetooth Smartphone devices carried by passengers at equipped transit-stops. A Kalman filtering formulation defined by the authors has been included in the application. The definition of the input for building the space-state model is linked to network scenarios modeled with the transportation planning platform EMME. The transit assignment framework is optimal strategy-based, which determines the subset of paths related to the optimal strategies between all OD pairsTaxi planning: a multiobjective oriented network design model for on ground aircraft's routing management
http://hdl.handle.net/2117/18027
Taxi planning: a multiobjective oriented network design model for on ground aircraft's routing management
Codina Sancho, Esteve; Marín, Ángel
In this paper a network design model is presented for the problem
of how to define an optimal airport topology in order to attend the conflicting
movements of the aircrafts on ground during short to medium planning periods
and taking into account the dynamic aspects of their interfering movements. Given
a set of decision variables affecting the airport’s topology, the model balances a set
of conflicting objectives or factors and their results are compared with the routing
decisions taken from real data. The model is primarily solved using ”B&B” and
the multicriteria approach presented is investigated using real test networks.
2013-03-01T10:05:43ZCodina Sancho, EsteveMarín, ÁngelIn this paper a network design model is presented for the problem
of how to define an optimal airport topology in order to attend the conflicting
movements of the aircrafts on ground during short to medium planning periods
and taking into account the dynamic aspects of their interfering movements. Given
a set of decision variables affecting the airport’s topology, the model balances a set
of conflicting objectives or factors and their results are compared with the routing
decisions taken from real data. The model is primarily solved using ”B&B” and
the multicriteria approach presented is investigated using real test networks.A multiobjective GRASP for the 1/3 variant of the time and space assembly line balancing problem
http://hdl.handle.net/2117/13842
A multiobjective GRASP for the 1/3 variant of the time and space assembly line balancing problem
Chica, Manuel; Cordon, Oscar; Damas, Sergio; Bautista Valhondo, Joaquín
Time and space assembly line balancing considers realistic multiobjective versions of the classical assembly line balancing industrial problems, involving the joint optimisation of conflicting criteria such as the cycle time, the number of stations, and/or the area of these stations. The aim of this contribution is to present a new algorithm, based on the GRASP methodology, for the 1/3 variant of this family of industrial problems. This variant involves the joint minimisation of the number and the area of the stations, given a fixed cycle time limit. The good behaviour of our proposal is demonstrated by means of performance indicators in four problem instances and a real one from a Nissan factory.
2011-11-10T11:00:29ZChica, ManuelCordon, OscarDamas, SergioBautista Valhondo, JoaquínTime and space assembly line balancing considers realistic multiobjective versions of the classical assembly line balancing industrial problems, involving the joint optimisation of conflicting criteria such as the cycle time, the number of stations, and/or the area of these stations. The aim of this contribution is to present a new algorithm, based on the GRASP methodology, for the 1/3 variant of this family of industrial problems. This variant involves the joint minimisation of the number and the area of the stations, given a fixed cycle time limit. The good behaviour of our proposal is demonstrated by means of performance indicators in four problem instances and a real one from a Nissan factory.Incorporating preferences to a multi-objective ant colony algorithm for time and space assembly line balancing
http://hdl.handle.net/2117/13841
Incorporating preferences to a multi-objective ant colony algorithm for time and space assembly line balancing
Chica, Manuel; Cordon, Oscar; Damas, Sergio; Pereira Gude, Jordi; Bautista Valhondo, Joaquín
We present an extension of a multi-objective algorithm based on Ant Colony Optimisation to solve a more realistic variant of a classical industrial problem: Time and Space Assembly Line Balancing. We study the influence of incorporating some domain knowledge by guiding the search process of the algorithm with preferences-based dominance. Our
approach is compared with other techniques, and every algorithm tackles a real-world instance from a Nissan plant. We prove that the embedded expert knowledge is even more justified in a real-world problem.
2011-11-10T10:43:43ZChica, ManuelCordon, OscarDamas, SergioPereira Gude, JordiBautista Valhondo, JoaquínWe present an extension of a multi-objective algorithm based on Ant Colony Optimisation to solve a more realistic variant of a classical industrial problem: Time and Space Assembly Line Balancing. We study the influence of incorporating some domain knowledge by guiding the search process of the algorithm with preferences-based dominance. Our
approach is compared with other techniques, and every algorithm tackles a real-world instance from a Nissan plant. We prove that the embedded expert knowledge is even more justified in a real-world problem.