Elevator Group Control During Morning Rush-Hours

Hikita, Shiro; Komaya, Kiyotoshi

doi:10.9746/sicetr1965.31.1896

Cited by 3 publications

(6 citation statements)

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“…This section describes tuning method for the learning parameters in order to achieve reinforcement learning, and shows experimental results obtained from comparison with conventional methods (Hikita and Komaya [5]). …”

Section: Methodsmentioning

confidence: 99%

“…A typical example of a system designed to accurately determine the number of elevators dispatched to the main floor during rush hour is the system of Hikita and Komaya [5]. In this system the following fuzzy rules are set based on several indices such as However, these fuzzy rules must be set in advance to correspond to the assumed environment and traffic pattern.…”

Section: Conventional Systems and Problemsmentioning

confidence: 99%

“…For comparison with the conventional system [5], the specification conditions in the proposed system were set to the same values. The system was set up in an imaginary standard office building having six functioning cages.…”

Section: Specifications Of Cages and Buildingmentioning

confidence: 99%

“…We have also conducted a simulation-based performance comparison in the same environment as in the system developed by Hikita and Komaya [5] which was shown to be very efficient in known studies pertaining to rush-hour traffic.…”

Section: Introductionmentioning

confidence: 99%

“…Later, other studies pursued innovation to those mainstream control methods based on wait time prediction and evaluation function: a study on control techniques using the expert system approach [4], and a study which demonstrated the efficiency of fuzzy theory approach to rush-hour traffic [5].…”

Section: Introductionmentioning

confidence: 99%

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Elevator group control system using multiagent system

Ogoshi¹,

Kimura²,

Hirose³

et al. 2002

Systems & Computers in Japan

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SUMMARYIn this study, the authors proposed an elevator group control system using multiagent system, and verified the efficiency of the system in areas characterized by concentration of large crowds of passengers on the main floor, for example, during morning rush-hour traffic. Congestion on the main floor in heavy morning rush-hour traffic areas was previously alleviated using specific traffic control systems providing so-called morning rush-hour operation by forced dispatching of multiple elevators to the main floor. However, since forced dispatching on the main floor affects areas other than the main floor and also the subsequent service on the main floor, it makes overall improvement of transportation efficiency a difficult task. There are published reports relating to morning rush-hour operation, but these deal with centralized control based on overall monitoring and sending instruction commands. Thus, the problem is that if this control system stopped working, it caused overall malfunctioning. In addition, in a system based on overall monitoring and generating optimal control plan in accordance with the received information, it is not easy to generate design updates following a change in the system's design or environment. Therefore, in the current study the authors introduced a multiagent system with distributed processing, in which individual elevators make action decisions by independent learning process. The authors proposed an elevator group control system which uses simplified reasoning to provide for flexible response even in the case of a changed environment, such as when a part of the elevator group has stopped functioning.

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Section: Methodsmentioning

confidence: 99%

Section: Conventional Systems and Problemsmentioning

confidence: 99%

Section: Specifications Of Cages and Buildingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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