Coherent configuration and operation of building transportation systems

Luh, Peter B.; Michel, Laurent; Santos, Eugene; Yu, Danqing; See, Andrew; Xiong, Bo; Johnson, Gregory P.; Chang, Soon-Jyh

doi:10.1109/coase.2005.1506765

Cited by 4 publications

(8 citation statements)

References 17 publications

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“…The overall down-peak traffic consists of 600 arrivals uniformly distributed in time and among floors in a 5-min interval. To minimize the overall egress time, this traffic is balanced between two stairs and the elevators by using a procedure such that the egress time via stairs is about the same as that via elevators [21]. The egress time via stairs is obtained by using probabilistic analysis with a given average passenger walking speed and stair width [21].…”

Section: Numerical Results and Insightsmentioning

confidence: 99%

“…For a given arrival rate, RTT in (19) is a function of which depends on , while is a function of RTT based on (20). In view of this nested relationship, an iterative procedure has been developed to calculate RTT and for a given arrival rate [21]. Note that the "threshold rate" at which the number of new arrivals within the interdeparture time equals the elevator capacity can be obtained as .…”

Section: A Extension For Up-peak With Little or No Future Informationmentioning

confidence: 99%

“…As mentioned above, the interdeparture time can be obtained for a given arrival rate. For our problem, the arrival rate is calculated as the number of passengers arrived during the past few (e.g., five) minutes plus the number of arrivals in the time window, then divided by the length of the interval considered [21].…”

Section: A Extension For Up-peak With Little or No Future Informationmentioning

confidence: 99%

“…To cover burst arrivals, elevators are "released" from the lobby when a certain percentage of elevator capacity is filled, i.e., (21) where is a user specified percentage of elevator capacity.…”

Section: A Extension For Up-peak With Little or No Future Informationmentioning

confidence: 99%

“…The overall egress time, i.e., the time required to evacuate all the occupants, depends on the percentages of floor populations assigned to elevators versus stairs. To balance the traffic between elevators and stairs, a heuristic procedure has been developed in [21], where the percentage of floor populations assigned to elevators is a truncated linear function of the floor number. Within this context, the elevator egress time ), i.e., the time required to evacuate occupants assigned to elevators, needs to be minimized.…”

Section: Scheduling For the Emergency Modementioning

confidence: 99%

See 4 more Smart Citations

Group Elevator Scheduling With Advance Information for Normal and Emergency Modes

Luh

Xiong

Chang

2008

IEEE Trans. Automat. Sci. Eng.

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Abstract-Group elevator scheduling has long been recognized as an important problem for building transportation efficiency, since unsatisfactory elevator service is one of the major complaints of building tenants. It now has a new significance driven by homeland security concerns. The problem, however, is difficult because of complicated elevator dynamics, uncertain traffic in various patterns, and the combinatorial nature of discrete optimization. With the advent of technologies, one important trend is to use advance information collected from devices such as destination entry, radio frequency identification, and sensor networks to reduce uncertainties and improve efficiency. How to effectively utilize such information remains an open and challenging issue. This paper presents the optimized scheduling of a group of elevators with destination entry and future traffic information for normal operations and coordinated emergency evacuation. Key problem characteristics are abstracted to establish a two-level separable formulation. A decomposition and coordination approach is then developed, where subproblems are solved by ordinal optimization-based local search, and top ranked nodes are selectively optimized by using dynamic programming. The approach is then extended to handle up-peak with little or no future traffic information, elevator parking for low intensity traffic, and coordinated emergency evacuation. Numerical testing results demonstrate near-optimal solution quality, computational efficiency, the value of future traffic information, and the potential of using elevators for emergency evacuation.Note to Practitioners-This paper studies group elevator scheduling with destination entry and future traffic information for normal operations, as well as for coordinated emergency evacuation. By exploiting the separable problem structure, a two-level formulation is established capable of modeling advance information. An approach is then developed by incorporating several innovative ideas into a decomposition and coordination framework, aiming to achieve near-optimal performance. The approach has also been extended for cases with little or no future traffic information and coordinated emergency evacuation. Numerical testing results are encouraging and further improvement is needed to reduce CPU time for online implementation.

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Section: Numerical Results and Insightsmentioning

confidence: 99%

Section: A Extension For Up-peak With Little or No Future Informationmentioning

confidence: 99%

Section: A Extension For Up-peak With Little or No Future Informationmentioning

confidence: 99%

Section: A Extension For Up-peak With Little or No Future Informationmentioning

confidence: 99%

Section: Scheduling For the Emergency Modementioning

confidence: 99%

See 3 more Smart Citations

Group Elevator Scheduling With Advance Information for Normal and Emergency Modes

Luh

Xiong

Chang

2008

IEEE Trans. Automat. Sci. Eng.

Self Cite

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Energy Saving of Elevator Group under Up-Peak Flow Based on Geese-PSO

Wang

Chen

2016

2016 7th International Conference on Cloud Computing and Big Data (CCBD)

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Energy-saving-oriented group-elevator dispatching strategy for multi-traffic patterns

Zhang

Zong

2014

Building Services Engineering Research and Technology

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Energy-saving elevator dispatching has been recognized as a challenging issue in building transportation, and we develop a novel energy-saving dispatching strategy for regenerative group-elevator system. Groupelevator dispatching is a typical combinatorial optimization problem, and three keys of the dispatching optimization are optimization method, objective, and model. The three keys of energy-saving-oriented elevator dispatching are studied in this paper. First, robust optimization method is introduced to handle dispatching optimization under uncertain elevator traffic flows; uncertain flows influence energy-saving dispatching seriously. Second, dispatching energy-objective function for regenerative group-elevator system is derived both schedule energy for four traffic patterns (up-peak, down-peak, up/down-mixed, and night) and return energy for two peak patterns (up-peak and down-peak) are considered. Third, four robust optimization-dispatching models for four traffic patterns are built, and optimization objectives of four models are minimizing the energy-objective function. Moreover, because we cannot solve robust optimization models with uncertain parameters directly, model counterpart transformation is studied. Finally, we solve the four transformed models by Linear Interactive and General Optimizer software and obtain robust optimization-dispatching solutions. In practice, four energy-saving-dispatching robust optimization models are switched according to real-time traffic patterns, and elevators are dispatched based on the dispatching solutions. We reduce elevator system-energy consumption effectively and keep average waiting time of the passengers acceptable under multi-traffic patterns. Simulation results demonstrate the validity of our strategy. Practical application: Group-elevator system spends much unnecessary energy because of the uncertainty of elevator passenger-traffic flows. This paper develops an energy-saving elevator-dispatching optimization strategy, which is immune to the uncertainty of four typical traffic flows. In practice, we update the group-elevator controller by our algorithm to realize energy-saving dispatching of regenerative groupelevator system under multi-traffic patterns.

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Coherent configuration and operation of building transportation systems

Cited by 4 publications

References 17 publications

Group Elevator Scheduling With Advance Information for Normal and Emergency Modes

Group Elevator Scheduling With Advance Information for Normal and Emergency Modes

Energy Saving of Elevator Group under Up-Peak Flow Based on Geese-PSO

Energy-saving-oriented group-elevator dispatching strategy for multi-traffic patterns

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