A simple and effective evolutionary algorithm for the vehicle routing problem

Prins, Christian

doi:10.1016/s0305-0548(03)00158-8

Cited by 845 publications

(482 citation statements)

References 10 publications

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“…First the IF are removed and then reinserted with DP. The method is based on that described by Beasley (1983) for a route-first, cluster-second method for the VRP that was also used in a genetic algorithm by Prins (2004). In our case the IF which is the closest one between two customers is considered for insertion.…”

Section: Local Searchmentioning

confidence: 99%

Models and Algorithms for the Integrated Planning of Bin Allocation and Vehicle Routing in Solid Waste Management

Hemmelmayr

Doerner

Hartl

et al. 2014

Transportation Science

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The efficient organization of waste collection systems based on bins located along the streets involves the solution of several tactical optimization problems. In particular, the bin configuration and sizing at each collection site as well as the service frequency over a given planning horizon have to be decided. In this context, a higher service frequency leads to higher routing costs, but at the same time less or smaller bins are required which lead to lower bin allocation investment costs. The bins used have different types and different costs and there is a limit on the space at each collection site as well as a limit on the total number of bins of each type that can be used. In this paper we consider the problem of designing a collection system consisting in the combination of a vehicle routing and a bin allocation problem in which the trade-off between the associated costs has to be considered. The solution approach combines an effective VNS metaheuristic for the routing part with a MILP-based exact method for the solution of the bin allocation part. We propose hierarchical solution procedures in which the two decision problems are solved in sequence, as well as an integrated approach where the two problems are considered simultaneously. Extensive computational testing on synthetic and real-world instances with hundreds of collection sites show the benefit of the integrated approaches with respect to the hierarchical ones.

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Section: Local Searchmentioning

confidence: 99%

Models and Algorithms for the Integrated Planning of Bin Allocation and Vehicle Routing in Solid Waste Management

Hemmelmayr

Doerner

Hartl

et al. 2014

Transportation Science

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“…These ingredients were shown powerful in (Prins, 2004) in designing efficient GA for vehicle-routing like problems.…”

Section: A Genetic Algorithmmentioning

confidence: 99%

“…It starts with the selection of two parents by binary tournament. The OX operator that was proved appropriate for VRP problems in (Prins, 2004) is then applied to generate two child chromosomes. These child chromosomes are evaluated by the exact split algorithm.…”

Section: A Genetic Algorithmmentioning

confidence: 99%

Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care

Liu

Xie

Augusto

et al. 2013

European Journal of Operational Research

230

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International audienceThis paper addresses a vehicle scheduling problem encountered in home health care logistics. It concerns the delivery of drugs and medical devices from the home care company's pharmacy to patients' homes, delivery of special drugs from a hospital to patients, pickup of bio samples and unused drugs and medical devices from patients. The problem can be considered as a special vehicle routing problem with simultaneous delivery and pickup and time windows, with four types of demands: delivery from depot to patient, delivery from a hospital to patient, pickup from a patient to depot and pickup from a patient to a medical lab. Each patient is visited by one vehicle and each vehicle visits each node at most once. Patients are associated with time windows and vehicles with capacity. Two mixed-integer programming models are proposed. We then propose a Genetic Algorithm (GA) and a Tabu Search (TS) method. The GA is based on a permutation chromosome, a split procedure and local search. The TS is based on route assignment attributes of patients, an augmented cost function, route re-optimization, and attribute-based aspiration levels. These approaches are tested on test instances derived from existing VRPTW benchmarks

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“…Exact solution methods for the CVRP are typically based on extensions of branch-and-cut (Lysgaard et al 2004), branch-and-cut-and-price (Fukasawa et al 2006) or set partitioning approaches (Baldacci et al 2008). Due to the computational challenges involved in solving the CVRP, a number of heuristic methods have been developed, such as iterative improvement local search algorithms Vigo 2003, Xu andKelly 1996), evolutionary algorithms (Prins 2004, Reimann et al 2004) and hybrid metaheuristic schemes, such as Memetic Algorithms (Nagata and Bräysy 2009) and Adaptive Memory Programming (Tarantilis 2005). …”

Section: Introductionmentioning

confidence: 99%

An Adaptive Memory Programming Framework for the Robust Capacitated Vehicle Routing Problem

Gounaris

Repoussis

Tarantilis

et al. 2016

Transportation Science

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We present an Adaptive Memory Programming (AMP) metaheuristic to address the Robust Capacitated Vehicle Routing Problem under demand uncertainty. Contrary to its deterministic counterpart, the robust formulation allows for uncertain customer demands, and the objective is to determine a minimum cost delivery plan that is feasible for all demand realizations within a prespecified uncertainty set. A crucial step in our heuristic is to verify the robust feasibility of a candidate route. For generic uncertainty sets, this step requires the solution of a convex optimization problem, which becomes computationally prohibitive for large instances. We present two classes of uncertainty sets for which route feasibility can be established much more efficiently. While we discuss our implementation in the context of the AMP framework, our techniques readily extend to other metaheuristics. Computational studies on standard literature benchmarks with up to 483 customers and 38 vehicles demonstrate that the proposed approach is able to quickly provide high quality solutions. In the process, we obtain new best solutions for a total of 123 benchmark instances.

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A simple and effective evolutionary algorithm for the vehicle routing problem

Cited by 845 publications

References 10 publications

Models and Algorithms for the Integrated Planning of Bin Allocation and Vehicle Routing in Solid Waste Management

Models and Algorithms for the Integrated Planning of Bin Allocation and Vehicle Routing in Solid Waste Management

Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care

An Adaptive Memory Programming Framework for the Robust Capacitated Vehicle Routing Problem

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