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    STUDIA INFORMATICA - Issue no. Sp.Issue 1 / 2009  
         
  Article:   A STEP-BACK SENSITIVE ANT MODEL FOR SOLVING COMPLEX PROBLEMS.

Authors:  CAMELIA CHIRA, CAMELIA-MIHAELA PINTEA, D. DUMITRESCU. 		 
       
         
  Abstract:  Ant colony optimization models are investigated with the aim of de-signing a new ant-based model better suited for real-world complex problems. The proposed Step-Back Sensitive Ant Model (SB-SAM) is inspired by the real behaviour of Lasius niger ants including u-turns in the process of selection. A ''step back'' is taken by an agent if it reaches a virtual state modulated by various sensitivity levels to the pheromone trails. An effective exploration of the search space is performed particularly by agents having low pheromone sensitivity while the exploitation of intermediary solutions is facilitated by highly-sensitive ants. Numerical experiments carried out for solving the Linear Ordering Problem em-phasize a better performance of the proposed SB-SAM algorithm compared to the Ant Colony System (ACS) technique.

Key words and phrases. Ant Colony System, Pheromone Sensitivity, Nature-inspired Metaheuristics.

  
         
     
         
         
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