A variety of hybrid genetic algorithms has been recently proposed to address the vehicle routing problem with time windows (VRPTW), a problme known to be NP-hard. However, very few genetic-based approaches exploit implicit knowledge provided by the strucutre of the intermediate solutions ocmputed during hte evolutionary process to explore the solution space. This paper presents a new hybrid gneetic algorithm for VRPTW. It investigates the impact of using explicitly domain knowledge and a priori knowledge/characteristics about expected solutions during the recombination and mutation phases of the algorithm. Basic principles borrow fro mrecent hybrid and standard genetic algorithms, and features of well-known heuristics to drive the search process. Designed to support time-constrained reasoning tasks, the procedure is intended to be conceptually simple, easy to implement and allow fast computation of near-optimal solution. A computational experiment has been conducted to compare the performance of the proposed algorithm with similar and standard techniques.
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