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 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

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

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 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

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 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

OTIMIZAÇÃO COM ALGORITMO BIO-INSPIRADO DE CONTROLE DE TRÁFEGO EM SISTEMAS DE GRUPOS DE ELEVADORES

Resumo. Este artigo tem como objetivo apresentar a implementação de uma técnica de otimização bioinspirada como solução ao problema de controle de tráfego em sistemas de grupos de elevadores (EGCS). A técnica de controle usada é o algoritmo de otimização por inteligência de enxame (PSO - swarm optimization particle) de tipo binário. A ideia é que o algoritmo escolha o melhor elevador para um usuário que faz uma chamada de serviço em umsistema de controle destino (DCS ”“ destination control system). Para a escolha do elevador o algoritmo tem uma função custo que considera as variáveis: (1) tempo de espera; (2) tempo de voo; (3) capacidade do elevador; (4) número de paradas alocadas; (5) número de paradas (baseado nas chamadas que são asignadas) para cada elevador. Estes parâmetros são ponderados de acordo com sua importância e inferência na seleção do melhor elevador. Assim, o sistema seleciona de todas as possíveis soluções encontradas a solução que apresenteo melhor valor de aptidão (a solução representa o elevador ou os elevadores selecionado para atender a atual chamada)

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms

Toplu taşıma sistemlerinin evrimsel algoritmalarla optimizasyonu

This study aims to examine, regulate, and update the land transportation of the Erzurum Metropolitan Municipality (EMM), Turkey using computerized calculation techniques. In line with these targets, some critical information has been obtained for study: the number of buses, the number of expeditions, the number of bus lines, and the number and maps of existing routes belonging to EMM. By using the information that has been obtained, this study aims at outlining specific outputs according to the input parameters, such as determining the optimal routes, the average travel, and the journey time. Once all of these situations were considered, various optimization algorithms were used to get the targeted outputs in response to the determined input parameters. In addition, the study found that the problem involved in modeling the land transport network of the EMM is in line with the so-called “traveling salesman problem,” which is a scenario about optimization often discussed in the literature. This study tried to solve this problem by using the genetic algorithm, the clonal selection algorithm, and the DNA computing algorithm. The location data for each bus stops on the bus lines selected for the study were obtained from the EMM, and the distances between these coordinates were obtained by using Google Maps via a Google API. These distances were stored in a distance matrix file and used as input parameters in the application and then were put through optimization algorithms developed initially on the MATLAB platform. The study’s results show that the algorithms developed for the proposed approaches work efficiently and that the distances for the selected bus lines can be shortened.Bu çalışma, Erzurum Büyükşehir Belediyesi'nin (EBB) Türkiye kara ulaşımını bilgisayarlı hesaplama teknikleri kullanarak incelemeyi, düzenlemeyi ve güncellemeyi amaçlamaktadır. Bu hedefler doğrultusunda, çalışma için bazı önemli bilgiler: otobüs sayısı, sefer sayısı, otobüs hattı sayısı ve EBB’ye ait mevcut güzergâh sayısı ve haritaları elde edilmiştir. Bu çalışma, elde edilen bilgileri kullanarak, optimal rotaların belirlenmesi, ortalama seyahat ve yolculuk süresi gibi girdi parametrelerine göre belirli çıktıların ana hatlarını çizmeyi amaçlamaktadır. Tüm bu durumlar göz önüne alındığında, belirlenen girdi parametrelerine karşılık hedeflenen çıktıları elde etmek için çeşitli optimizasyon algoritmaları kullanılmıştır. Çalışma, EBB’ nin ulaşım ağının modellenmesindeki problemin, literatürde sıklıkla tartışılan optimizasyonla ilgili bir senaryo olan “gezgin satıcı problemi” ile uyumlu olduğunu bulmuştur. Çalışmada genetik algoritma, klonal seçim algoritması ve DNA hesaplama algoritması kullanılarak bu problem çözülmeye çalışılmıştır. Çalışmada seçilen otobüs hatlarındaki her bir durak için konum bilgisi EBB'den alınmış ve bu koordinatlar arasındaki mesafeler bir Google API üzerinden Google Maps kullanılarak elde edilmiştir. Bu mesafeler bir mesafe matrisi dosyasında saklanmış ve uygulamada giriş parametreleri olarak kullanılmış daha sonra MATLAB platformunda geliştirilen optimizasyon algoritmalarına aktarılmıştır. Çalışmanın sonuçları, önerilen yaklaşımlar için geliştirilen algoritmaların verimli çalıştığını ve seçilen otobüs hatları için mesafelerin kısaltılabileceğini göstermektedir