Authors:
Juha-Matti Kuusinen
;
Mirko Ruokokoski
;
Janne Sorsa
and
Marja-Liisa Siikonen
Affiliation:
KONE Corporation, Finland
Keyword(s):
Elevator traffic, Origin-destination Matrix, Linear Programming, Branch-and-bound.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
e-Business
;
Enterprise Information Systems
;
Industrial Engineering
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Linear Programming
;
Logistics
;
Mathematical Modeling
;
Methodologies and Technologies
;
Network Optimization
;
Operational Research
;
Optimization
;
OR in Transportation
;
Pattern Recognition
;
Software Engineering
;
Symbolic Systems
Abstract:
Elevator group control dispatches elevators to passengers’ calls in a dynamic environment where new calls constantly emerge. At the moment of making a dispatching decision, it is not known when and at which floors new passengers will register new calls, what is the number of passengers waiting behind these and existing calls, and what are their destinations. Robust dispatching decisions require that future passenger traffic is
forecast based on the realized passenger flow in a building. The problem is that this flow cannot be directly measured. It can, however, be estimated by finding the passenger counts for the origins and destinations of every elevator trip occurring in a building. An elevator trip consists of successive stops in one direction of travel with passengers inside the elevator. We formulate the elevator trip origin-destination matrix estimation
problem as a minimum cost network flow problem. We also present a branch-and-bound algorithm for finding all solutions to the
problem and study its performance based on numerical experiments.
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