339 research outputs found
Vertical transportation in buildings
Nowadays, the building industry and its associated technologies are
experiencing a period of rapid growth, which requires an equivalent growth regarding
technologies in the field of vertical transportation. Therefore, the installation of
synchronised elevator groups in modern buildings is a common practice in order to
govern the dispatching, allocation and movement of the cars shaping the group. So,
elevator control and management has become a major field of application for Artificial
Intelligence approaches. Methodologies such as fuzzy logic, artificial neural networks,
genetic algorithms, ant colonies, or multiagent systems are being successfully proposed
in the scientific literature, and are being adopted by the leading elevator companies as
elements that differentiate them from their competitors. In this sense, the most relevant
companies are adopting strategies based on the protection of their discoveries and
inventions as registered patents in different countries throughout the world. This paper
presents a comprehensive state of the art of the most relevant recent patents on
computer science applied to vertical transportationConsejería de Innovación, Ciencia y Empresa, Junta de Andalucía P07-TEP-02832, Spain
Evolutionary Networks for Multi-Behavioural Robot Control : A thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science Massey University, Albany, New Zealand
Artificial Intelligence can be applied to a wide variety of real world problems, with
varying levels of complexity; nonetheless, real world problems often demand for
capabilities that are difficult, if not impossible to achieve using a single Artificial
Intelligence algorithm. This challenge gave rise to the development of hybrid systems
that put together a combination of complementary algorithms. Hybrid approaches
come at a cost however, as they introduce additional complications for the developer,
such as how the algorithms should interact and when the independent algorithms
should be executed. This research introduces a new algorithm called Cascading
Genetic Network Programming (CGNP), which contains significant changes to the
original Genetic Network Programming. This new algorithm has the facility to
include any Artificial Intelligence algorithm into its directed graph network, as either
a judgement or processing node. CGNP introduces a novel ability for a scalable
multiple layer network, of independent instances of the CGNP algorithm itself. This
facilitates problem subdivision, independent optimisation of these underlying layers
and the ability to develop varying levels of complexity, from individual motor control
to high level dynamic role allocation systems. Mechanisms are incorporated to
prevent the child networks from executing beyond their requirement, allowing the
parent to maintain control. The ability to optimise any data within each node
is added, allowing for general purpose node development and therefore allowing
node reuse in a wide variety of applications without modification. The abilities
of the Cascaded Genetic Network Programming algorithm are demonstrated and
proved through the development of a multi-behavioural robot soccer goal keeper, as
a testbed where an individual Artificial Intelligence system may not be sufficient.
The overall role is subdivided into three components and individually optimised
which allow the robot to pursue a target object or location, rotate towards a target
and provide basic functionality for defending a goal. These three components are
then used in a higher level network as independent nodes, to solve the overall multi-
behavioural goal keeper. Experiments show that the resulting controller defends the
goal with a success rate of 91%, after 12 hours training using a population of 400
and 60 generations
Hybrid of multi-car elevator system and double-deck elevator system
Multi-car elevator system is a new breakthrough in an elevator system in 2001. It has broken the traditional concept of developing only one elevator car in an elevator shaft. Multi-car elevator system can have more than one elevator car moving in an elevator shaft and it has improved a lot in minimizing the waiting time of passengers if compared with only one elevator car in an elevator shaft. The main advantage of multi-car elevator system is to reduce the construction cost where 30% of the core-tube area of the elevator system is made up of shaft. By developing multi-car elevator system, many of elevator shafts need not to be developed and it still can perform about the same efficiency in serving passengers. However, it is still not able to transport a large number of passengers efficiently if the passengers are calling from the same floor, especially during the up-peak traffic. For that reason, the feature of double-deck elevator system is integrated into multi-car elevator system to develop a new hybridized elevator system called “Hybrid of multi-car elevator system and double-deck elevator system” to solve the limited car capacity problem. The performance of both systems, the hybridized elevator system and the multi-car elevator system is simulated. The result shows that the average journey time of the hybridized elevator system is shorter than the multicar elevator system in all the three traffic modes, i.e. up-peak, down-peak and inter-floor traffics. For the up-peak traffic mode of the hybridized elevator system, it manages to achieve the best result of 33.5% shorter of the average journey time compared to the multi-car elevator system
Una revisión del estado del arte de los problemas asociados al transporte vertical mediante ascensores en edificios
El transporte vertical es una disciplina que estudia los movimientos de personas en edificios. Los edificios altos se han convertido en una construcción común hoy en día. En dichos edificios, el transporte vertical es un problema que requiere un enfoque
sistemático y ordenado. Así, para casos extremos en determinados edificios singulares, la ordenación del transporte vertical se
convierte en un problema muy difícil de manejar, especialmente cuando diferentes personas llegan casi al mismo tiempo a plantas
específicas deseando viajar hasta otras plantas de destino. Para resolver tales situaciones, la instalación de sistemas de control de
grupos de ascensores (conocidos en inglés como Elevator Group Control Systems, EGCS) es una práctica habitual. Los EGCS se
utilizan para gestionar ascensores coordinados múltiples en un edificio con el objeto de transportar pasajeros de manera eficiente.
Los EGCS deben satisfacer las demandas asignando un ascensor a cada llamada de planta, realizando el despacho de ascensores
atendiendo a diferentes criterios de optimización. Este artículo realiza una revisión sistemática y muestra distintas clasificaciones
de las contribuciones más relevantes en la industria del transporte vertical, abordando tanto la revisión de la literatura científica,
como las patentes en la industria y los trabajos recogidos en revistas de carácter profesional.Plan Nacional de I+D TI-331/2002Plan Nacional de I+D DPI2010- 15352Consejería de Innovación, Ciencia y Empresa de la Junta de Andalucía P07-TEP-0283
A brief review on vertical transportation research and open issue
Book of Proceedings of the International Joint Conference-CIO-ICIEOM-IIE-AIM (IJC 2016), "XX Congreso de Ingeniería de Organización", "XXII International Conference on Industrial Engineering and Operations Management, "International IISE Conference 2016, "International AIM Conference 2016". Donostia-San Sebastian (Spain), July 13-15, 2016Vertical transportation refers to the movements of people in buildings.
High-rise buildings have emerged as a common construction nowadays. In such
buildings, the vertical transportation is extremely difficult to manage, specially,
when the people arrive at the same time at specific floors wanting to travel to other
floors. To solve such situations, the installation of elevator group control systems
(EGCS) is a usual practice. EGCS are used to manage multiple elevators in a building
to efficiently transport passengers. EGCSs need to meet the demands by assigning
an elevator to each landing call while optimizing several criteria. This paper
reviews the most relevant contributions in vertical transportation industr
Dynamic fuzzy logic elevator group control system for energy optimization
High-rise buildings with a considerable number of elevators represent a major logistic problem
concerning saving space and time due to economic reasons. For this reason, complex Elevator Group
Control Systems are developed in order to manage the elevators properly. Furthermore, the subject
of energy is acquiring more and more industrial relevance every day as far as sustainable
development is concerned.
In this paper, the first entirely dynamic Fuzzy Logic Elevator Group Control System to dispatch
landing calls so as to minimize energy consumption, especially during interfloor traffic, is proposed.
The fuzzy logic design described here constitutes not only an innovative solution that outperforms
usual dispatchers but also an easy, cheap, feasible and reliable solution, which is possible to be
implemented in real industry controllers
A particle swarm optimization algorithm for optimal car-call allocation in elevator group control systems
High-rise buildings require the installation of complex elevator group control
systems (EGCS). In vertical transportation, when a passenger makes a hall call by pressing a
landing call button installed at the floor and located near the cars of the elevator group, the
EGCS must allocate one of the cars of the group to the hall call. We develop a Particle Swarm
Optimization (PSO) algorithm to deal with this car-call allocation problem. The PSO algorithm
is compared to other soft computing techniques such as genetic algorithm and tabu search
approaches that have been proved as efficient algorithms for this problem. The proposed PSO
algorithm was tested in high-rise buildings from 10 to 24 floors, and several car configurations
from 2 to 6 cars. Results from trials show that the proposed PSO algorithm results in better
average journey times and computational times compared to genetic and tabu search
approaches
A review of multi-car elevator system
This paper presents a review of a new generation of elevator system, the Multi-Car Elevator System. It is an elevator system which contains more than one elevator car in the elevator shaft. In the introduction, it explains why the Multi-Car Elevator System is a new trend elevator system based on its structural design, cost saving and efficiency in elevator system. Different types of Multi-Car Elevator System such as circulation or loop-type, non-circulation and bifurcate circulation are described in section 2. In section 3, researches on dispatch strategies, control strategies and avoidance of car collision strategies of Multi-Car Elevator System since 2002 are reviewed. In the discussion section, it reveals some drawbacks of the Multi-Car Elevator System in transport capability and the risk of car collision. There are recommendations to the future work as well
A viral system algorithm to optimize the car dispatching in elevator group control systems of tall buildings
Nowadays is very common the presence of tall buildings in the business centres of
the main cities of the world. Such buildings require the installation of numerous lifts that are
coordinated and managed under a unique control system. Population working in the buildings
follows a similar traffic pattern generating situations of traffic congestion. The problem arises
when a passenger makes a hall call wishing to travel to another floor of the building. The
dispatching of the most suitable car is the optimization problem we are tackling in this paper.
We develop a viral system algorithm which is based on a bio-inspired virus infection analogy to
deal with it. The viral system algorithm is compared to genetic algorithms, and tabu search
approaches that have proven efficiency in the vertical transportation literature. The
experiments undertaken in tall buildings from 10 to 24 floors, and several car configurations
from 2 to 6 cars, provide valuable results and show how viral system outperforms such soft
computing algorithms.Plan Estatal de Investigación Científica y Técnica y de Innovación (España
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