An ACO model for a non-stationary formulation of the single elevator problem


  • Silvia Molina Universidad Nacional de San Luis, (5700) San Luis, Argentina
  • Mario Guillermo Leguizamón Universidad Nacional de San Luis, (5700) San Luis, Argentina
  • Enrique Alba Torres Universidad de Málaga, Complejo Tecnológico - Campus de Teatinos, Málaga, Españaa


Ant Colony Optimization (ACO), Single Elevator Problem (SEP), Non-stationary Problems, Ant Colony System design


The Ant Colony Optimization (ACO) metaheuristic is a bio-inspired approach for hard combinatorial optimization problems for stationary and non-stationary environments. In the ACO metaheuristic, a colony of artificial ants cooperate for finding high quality solutions in a reasonable time. An interesting example of a non-stationary combinatorial optimization problem is the Multiple Elevators Problem (MEP) which consists in finding a sequence of movements for each elevator to perform in a building so that to minimize, for instance, the users waiting average time. Events like the arrival of one new user to the elevator queue or the fault of one elevator dynamically produce changes of state in this problem. A subclass of MEP is the the so called Single Elevator Problem (SEP). In this work, we propose the design of an ACO model for the SEP that can be implemented as an Ant Colony System (ACS). Keywords: Ant Colony Optimization, Single Elevator Problem, Non-stationary Problems, Ant Colony System design.


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How to Cite

Molina, S., Leguizamón, M. G., & Alba Torres, E. (2007). An ACO model for a non-stationary formulation of the single elevator problem. Journal of Computer Science and Technology, 7(01), p. 41–51. Retrieved from



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