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The paper introduces a bio-inspired approach to solve the route allocation problem (RAP) in the transportation networks. The approach extends a well-known meta-heuristics algorithm with the real life constraints that are dealt with in the scheduling process (i.e. the uniform distribution of routes diversity for vehicles, the average distance travelled in a month, the driver’s rest between subsequent trips etc.). The paper is focusing on the engineering aspects of employing bio-inspired algorithms (which proved to have near-optimal results for toy-like problems) to a real-life application domain. The approach proved to be capable of preserving the software components (agents) to the complexity and dynamics of the situation when the RAP requires incremental extensions of constraints to reflect the traffic conditions in the transportation network. [ABSTRACT FROM AUTHOR]