Solving a heterogeneous fleet multi-compartment vehicle routing problem:a case study

Efthymiadis, Simos; Liapis, Nikolaos; Nenes, George

doi:10.1080/23302674.2023.2190474

Cited by 4 publications

(2 citation statements)

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“…First, they developed an accurate algorithm for MCVRP with a single depot and heterogeneous fleet [22] , then further considered MCVRP [23] with the limited number of vehicles, and then discussed MCVRP with time window, and proposed two heuristic algorithms [24] . In 2012, Cornillier et al [25] further studied a more practical MCVRP for fuel delivery in which they consider multiple depots, heterogeneous fleet, the limited number of vehicles, hard time window, multitrips, unsplit compartments, unsplit tanks, and the gas station that can only be visited once by a vehicle. Wang et al [12] described a model for the fuel replenishment problem (FRP), which considers multi-compartments trucks, a heterogeneous fleet, multiple trips of each truck, and hard time window.…”

Section: Vrp For Multiple Compartments Vehiclesmentioning

confidence: 99%

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Multi-Compartment Electric Vehicle Routing Problem for Perishable Products

Liu,

Li,

et al. 2024

Int. J. Crowd Sci.

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The study first proposes a heterogeneous fleet, multi-compartment electric vehicle routing problem for perishable products (MCEVRP-PP). We capture a lot of practical demands and constraints of the MCEVRP-PP, such as multiple temperature zones, the hard time window, charging more than once during delivery, various power consumption per unit of refrigeration, etc. We model the MCEVRP-PP as a mixed integer program and aim to optimize the total cost including vehicle fixed cost, power cost, and cooling cost. A hybrid ant colony optimization (HACO) is developed to solve the problem. In the transfer rule, the time window is introduced to improve flexibility in route construction. According to the features of multi-compartment electric vehicles, the capacity constraint judgment algorithm is developed in route construction. Six local search strategies are designed with time windows, recharging stations, etc. Experiments based on various instances validate that HACO solves MCEVRP-PP more effectively than the ant colony optimization (ACO). Compared with fuel vehicles and single-compartment vehicles, electric vehicles and multicompartment electric vehicles can save the total cost and mileage, and increase utilization of vehicles.

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Section: Vrp For Multiple Compartments Vehiclesmentioning

confidence: 99%

“…Constraints (23) and (24) represent the relationship between variables. Constraint (25) guarantees that each compartment is loaded with at most one product segment. The compartment is allowed to be empty.…”

Section: ) Decision Variablementioning

confidence: 99%