<p>Nowadays, traveling has become a routine activity for many people, so that many researchers have developed studies in the tourism domain, especially for the determination of tourist routes. Based on prior work, the problem of determining travel route is analogous to finding the solution for travelling salesman problem (TSP). However, the majority of works only dealt with generating the travel route within one day and also did not take into account several user’s preference criteria. This paper proposes a model for generating a travel route schedule within a few days, and considers some user needs criteria, so that the determination of a travel route can be considered as a multi-criteria issue. The travel route is generated based on several constraints, such as travel time limits per day, opening/closing hours and the average length of visit for each tourist destination. We use simulated annealing method to generate the optimum travel route. Based on evaluation result, the optimality of the travel route generated by the system is not significantly different with ant colony result. However, our model is far more superior in running time compared to Ant Colony method.</p>
Self-organization has been proposed to be implemented in complex systems which require the automation capabilities to govern itself and to adapt upon changes. Self-organizing systems can be modeled as multi-agent systems (MAS) since they share common characteristics in that they consist of multiple autonomous systems. However, most existing MAS engineering methodologies do not fully support self-organizing systems design since they require predefined goals and agent behaviors, which is not the case in self-organizing systems. Another feature that is currently not supported for designing self-organizing MAS is the separation between the design of agent behaviors and behavior adaptation, i.e. how agents adapt their behaviors to respond upon changes. To tackle these issues, this paper proposes a role modeling method, in which agent behaviors are represented as roles, to design how agents perform behavior adaptation at runtime by switching between roles. The applicability of the proposed role modeling method is evaluated in a case study of a self-organizing smart transportation system.
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