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The objective of global optimality versus the cost that this implies is an unresolved issue by researchers. Classical problems such as travel salesman problem (TSP) or vehicle routing problem (VRP) and it's derivatives, relate to combinatorial optimization problems that arise on an everyday basis for a group of people that would like to have the solution to such problems as soon as possible. Thus, the idea that such problems purely operational, would be solved by heuristics in devices makes sense, due to the interest of normal use for sellers or car's drivers. Within the framework of what we may call ubiquitous distributed computing, this paper proposes an BDI architecture that supports the resolution of problems in complex combinatorial mobile devices across heuristics or metaheuristics embedded in the devices themselves and working from a set of data from a central server using agents for coordination and collaboration.