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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]

Ant colony system is a metaheuristic algorithm inspired by the behavior of real ants and was proposed by Dorigo et al. as a method for solving hard combinatorial optimization problems. In this paper we show its successful application to solving a network design problem: Generalized Vehicle Routing Problem. The Generalized Vehicle Routing Problem (GVRP) is the problem of designing optimal delivery or collection routes, subject to capacity restrictions, from a given depot to a number of predefined, mutually exclusive and exhaustive clusters. Computational results for several benchmark problems are reported. [ABSTRACT FROM AUTHOR]

In this paper I give a survey on some results about optimality criteria (also approximate) in vector optimization. A special attention is dedicated to a new approach to approximate solutions for multicriteria situations as recently given in L. Pusillo and S. Tijs 2009. [ABSTRACT FROM AUTHOR]