More and more companies in the routing industry are providing consistent service to gain competitive advantage. However, improved service consistency comes at the price of higher routing cost, i.e., routing cost and service consistency are conflicting objectives. In this paper, we extend the generalized consistent vehicle routing problem (GenConVRP) by considering several objective functions: improving driver consistency and arrival time consistency, and minimizing routing cost are independent objectives of the problem. We refer to the problem as the multi-objective generalized consistent vehicle routing problem (MOGenConVRP). A multi-objective optimization approach enables a thorough trade-off analysis between the conflicting objective functions. The results of this paper should help companies in finding adequate consistency goals to aim for. Results are generated for several test instances by two exact solution approaches and one heuristic. The exact approaches are based on the ϵ -constraint framework and are used to solve small test instances to optimality. Large instances with up to 199 customers and a planning horizon of 5 days are solved by multi directional large neighborhood search (MDLNS) that combines the multi directional local search framework and the LNS for the GenConVRP. The solution quality of the heuristic is evaluated by examining five multi-objective quality indicators. We find that MDLNS is an eligible solution approach for performing a meaningful trade-off analysis. Our analysis shows that a 70 percent better arrival time consistency is achieved by increasing travel cost by not more than 3.84 percent, on average; visiting each customer by the same driver each time is significantly more expensive than allowing at least two different drivers per customer; in many cases, arrival time consistency and driver consistency can be improved simultaneously. 
The multi-objective generalized consistent vehicle routing problem