We present a hybrid tabu search variable neighborhood (HVNTS) heuristic that chooses Pareto nondominated solutions satisfying a set of Nash equilibrium conditions for a multiple-agent game theory model. The framework is general and can tackle different classes of Vehicle Routing Problems (VRP). It is here in applied to the VRP with Multiple Time Windows (VRPMTW) and tested on three objectives: minimizing the total travel cost (expressed in time units), maximizing the minimal customers’ utility, and maximizing the minimal drivers’ utility. The results for benchmark instances highlight the benefits of the multiple criteria model.
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