Heterogeneous Fleet Vehicle Routing Problem with Synchronization Constraints




The context of home healthcare services, patients may need to be visited multiple times by different healthcare specialists who may use a fleet of heterogeneous vehicles. In addition, some of these visits may need to be synchronized to provide the best service by more than one specialist at the same time. This gives rise to a new variant of the Vehicle Routing Problem (VRP), which we call the Heterogeneous Fleet Vehicle Routing Problem with Synchronized visits (HF-VRPS).  The problem consists of planning a set of routes for a fleet of heterogeneous Light Duty Vehicles (LDV), composed of Alternative Fuel Vehicles (AFVs) instead of conventional vehicles.  We present an integer linear-programming formulation for this problem and propose three population-based hybrid Artificial Bee Colony (ABC) metaheuristic algorithms. These variants include Demon Algorithm, Old Bachelor Acceptance, and Record-to-Record Travel algorithms that are each hybridized with the ABC. To evaluate the proposed metaheuristics, we generated new test instances and used a set of the VRPS instances from the literature. The results show that our proposed algorithms produce good-quality solutions. Moreover, our experimental results illustrate the trade-offs between important problem factors, such as fuel emission, fuel consumption, and drivers’ costs. The computational results also demonstrate the advantage of adopting a heterogeneous fleet rather than a homogeneous one.

Keywords: Combinatorial optimization; Vehicle routing problem with synchronization; Green logistics; Metaheuristic algorithms; Artificial Bee Colony algorithm


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