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

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

Optimal dispatching of elevators employing the consideration of relative time

El presente artículo expone, primero desde de un punto de vista teórico y matemático, las bases de nuevo controlador para la optimización del despacho de ascensores en un edificio teniendo en cuenta lo que se denomina el tiempo relativo, es decir no sólo se tiene en cuenta el tiempo que una cabina tardaría en atender una llamada considerada, sino que además se tiene en cuenta el impacto (la modificación de los tiempos de espera) que esta opción de despacho tendría sobre las demás opciones. Finalmente la validez del algoritmo de despacho es ratificada mediante simulación.The article puts forward the idea of a novel elevator group control system that takes into account not only the time a lift spends responding to a call but the impact this allocation option have over all the dispatching options. Firstly the proposed algorithm is justified in mathematical and theoretical terms and finally its performance is demonstrated via computer simulation

Intelligent strategies for mobile robotics in laboratory automation

In this thesis a new intelligent framework is presented for the mobile robots in laboratory automation, which includes: a new multi-floor indoor navigation method is presented and an intelligent multi-floor path planning is proposed; a new signal filtering method is presented for the robots to forecast their indoor coordinates; a new human feature based strategy is proposed for the robot-human smart collision avoidance; a new robot power forecasting method is proposed to decide a distributed transportation task; a new blind approach is presented for the arm manipulations for the robots

Comparing Elevator Strategies for a Parking Lot

In this paper, we compare elevator strategies for a parking garage. It is assumed that the parking garage has several floors and there is an elevator which can stop on each floor. We begin by considering 4 strategies detailed in page 23. For each strategy, we loop the program 100 times, and get 100 mean values for wait times. Welch\u27s test confirms highly significant differences among the 4 strategies. Repeating the analysis multiple times we see that the best of the 4 strategies is strategy 2, which places the elevator on floor 2 (the median floor) after use

Framework to Explore the Design Space for Design of Tall Buildings

Design of tall buildings is undergoing a resurgence that is driven by a variety of factors – economical growth, scarcity of land in urban areas, high land costs, increased population density, technological advancements and man’s desire to build taller structures. Considerable research work has been done in the last two decades to meet this demand. Computer-based tools that help design engineers explore design alternatives are indispensable in tackling this complex problem. In addition, a framework that finds the near optimal design, adds value to this exploratory work. In this paper, we develop a general framework for the design optimization of buildings using sizing, shape, and topology design variables. Sizing optimization can be carried out using discrete design variables (from a database of available sections) or continuous design variables (cross-sectional dimensions of custom wide flange sections). Similarly, shape optimization can be carried out using either discrete or continuous design variables. And finally, topology optimization can be carried out using boolean design variables. Allowable stress design guidelines are used as constraints along with displacement, inter-story drift, total structural weight, and frequency constraints. The finite element model is made of three-dimensional beam elements. A typical function evaluation involves a linear, static analysis with multiple load cases, a linear, modal analysis to extract the lowest few eigenpairs, and a linear, buckling analysis to find the buckling capacity. An optimization toolbox that contains gradient-based and population-based optimizers, is a part of the framework. Numerical results how that the framework is capable of producing efficient designs effectivel