GA BASED HYBRID FUZZY RULE OPTIMIZATION APPROACH FOR ELEVATOR GROUP CONTROL SYSTEM

2013 ◽  
Vol 37 (3) ◽  
pp. 937-947 ◽  
Author(s):  
Ta-Cheng Chen ◽  
Yuan-Yong Hsu ◽  
An-Chen Lee ◽  
Shiang-Yu Wang
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Service Quality ◽  
Fuzzy Rule ◽  
Optimization Approach ◽  
Rule Based ◽  
Group Control ◽  
Elevator Group Control ◽  
Traditional Approaches ◽  
Rule Optimization

Elevators are the essential transportation tools in high buildings so that elevator group control system (EGCS) is developed to dynamically layout the schedule of elevators in a group. In this study, a fuzzy rule based intelligent EGCS optimized by genetic algorithm has been proposed where the rules with the corresponding parameters are generated optimally so as to maximize service quality. The experimental results show that the performance of our approach is superior to these of traditional approaches in the literature.

GA Based Hybrid Fuzzy Rule Optimization Approach for Elevator Group Control System

2013 ◽  
Vol 284-287 ◽  
pp. 2380-2384 ◽  
Author(s):  
Ta Cheng Chen ◽  
Yuan Yong Hsu ◽  
An Chen Lee ◽  
Shiang Yu Wang
Keyword(s):  
Control System ◽  
Flow Direction ◽  
Fuzzy Rule ◽  
Fuzzy Rules ◽  
Optimization Approach ◽  
Department Stores ◽  
Rule Based ◽  
Group Control ◽  
Rule Set ◽  
Elevator Group Control

Elevators are the essential transportation tools in high buildings so that Elevator Group Control System (EGCS) is developed to dynamically layout the schedule of elevators in a group. In this study, a fuzzy rules based intelligent elevator group control system has been proposed in which the structure of rules including the related parameters are generated optimally based on the traffic data so as to maximize service quality. In literature, the fuzzy related approaches have been applied in EGCS but the fuzzy rules were all pre-defined. However, how to create the most suitable fuzzy rule set in EGCS for dispatching elevators more efficiently and economically are never discussed in literature. The aim of the proposed approach is to minimize the average waiting time at peak hours as well as to minimize the power energy at off-peak hours by using the proposed fuzzy rule based ECGS. Moreover, there are many decision variables are considered in the GCGS to provide the most appropriate elevator assignment whenever any hall call is given. These variables include the number of elevators, traffic flow, direction, passenger preferences (for instance, department stores, hospitals, hotels, and office buildings), congestion and VIP priority floor, etc. In this study, a fuzzy rule based elevator-dispatching approach has been proposed for the EGCS in which the fuzzy rules and related parameters are derived optimally by using genetic algorithm based on the historical elevator transportation data. The experimental results show that the performance of the proposed approach is superior to these of traditional approaches in literatures.

Twin Elevator Group Optimization Dispatching Based on Genetic Algorithm

2013 ◽  
Vol 415 ◽  
pp. 95-100
Author(s):  
Bao Ding ◽  
Qing Chao Li ◽  
Jin Zhang ◽  
Xiao Feng Liu
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Waiting Time ◽  
Theoretical Basis ◽  
Engineering Application ◽  
Time Algorithm ◽  
Structure Characteristics ◽  
Group Control ◽  
Objective Control ◽  
Elevator Group Control

For the characteristics of a new elevator twin elevator with multiple objectives and uncertainty of group control system ,this work proposed a method of twin elevator group optimization dispatching based on genetic algorithm (GA). On the basis of the analysis of structure characteristics of twin elevator, by means of putting twin elevator running rules into the multi-objective control strategy, the method constructed objective function for twin elevator group; the method utilized GA for the simulation of twin elevator group optimization dispatching, and compared it with the minimum waiting time algorithm. Research results show that the method is able to adapt to the running characteristics of twin elevator, and different traffic flow pattern. Compared with the ones of the minimum waiting time algorithm, average waiting time, long waiting time incidence and the numbers of elevator stops of genetic algorithm are all significantly reduced. Consequently, this method has a strong ability to adapt, and provides a theoretical basis for engineering application of twin elevator group control system.

Optimizing the Intelligent Elevator Group Control System by Using Genetic Algorithm

2012 ◽  
Vol 9 (1) ◽  
pp. 957-962 ◽  
Author(s):  
Ta-Cheng Chen ◽  
Yuan-Yong Hsu ◽  
Yi-Ju Huang
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Group Control ◽  
Elevator Group Control

Application of Multi-Objective Artificial Immune Optimal Algorithm in the Elevator Group Control System

2011 ◽  
Vol 130-134 ◽  
pp. 3557-3561
Author(s):  
Yue Min Liu ◽  
Yan Zhu
Keyword(s):  
Control System ◽  
Service Quality ◽  
Hybrid Algorithm ◽  
Immune Algorithm ◽  
Artificial Immune ◽  
Artificial Immune Algorithm ◽  
Multi Objective ◽  
Group Control ◽  
Elevator Group Control ◽  
Weighted Values

With the development of the electronic technology, people have proposed higher requirements for the service quality on elevator, and the optimal elevator dispatching has developed a typical multi-objective optimal process. This paper analyzes both the advantages and the disadvantages of artificial immune algorithm and gradient descent algorithm, optimizes artificial immune algorithm, then proposes a novel optimal hybrid algorithm; at the same time, uses this hybrid algorithm in the elevator group control system combined with Pareto solution set. Making a comparison between the hybrid algorithm and the standard artificial immune algorithm, it’s clear that this hybrid algorithm has certain feasibility and superiority, and to some extent, has improved the overall performance and service quality of the elevator group control system. This paper has provided a new method and a new thought on determination of the multi-objective weighted values in the elevator group control system.

A parameter tuning method for an elevator group control system using a genetic algorithm

1998 ◽  
Vol 124 (1) ◽  
pp. 55-64 ◽  
Author(s):  
Toshimitsu Tobita ◽  
Atsuya Fujino ◽  
Kazuhiro Segawa ◽  
Kenji Yoneda ◽  
Yoshiaki Ichikawa
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Parameter Tuning ◽  
Tuning Method ◽  
Group Control ◽  
Elevator Group Control

The Intelligent Scheduling Method of Elevator Group Control Based on Fuzzy Neural Network

2012 ◽  
Vol 155-156 ◽  
pp. 653-657
Author(s):  
Yu Lin Dong ◽  
Xiao Ming Wang
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Scheduling Algorithm ◽  
Mathematic Model ◽  
Group Control ◽  
Fuzzy Neural ◽  
And Performance ◽  
Elevator Group Control

Elevator group control system (EGCS) is a complex optimization system, which has the characteristics of multi-objective, uncertain, stochastic random decision-making and nonlinear. It is hard to describe the elevator group control system in exact mathematic model and to increase the capability of the system with traditional control method. In this paper, we aim at the characters of elevator group control system and intelligent control, introduce the system's control fashion and performance evaluate guidelines and propose an elevator group control scheduling algorithm based on fuzzy neural network.

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