Modeling and solving the fuel distribution problem with unloading precedence and loading sequence considerations

Konstantinos N. Androutsopoulos () and Konstantinos G. Zografos ()
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Konstantinos N. Androutsopoulos: Athens University of Economics and Business
Konstantinos G. Zografos: Lancaster University Management School

Annals of Operations Research, 2024, vol. 332, issue 1, No 33, 909-947

Abstract: Abstract This paper presents a real-world liquid fuel distribution problem involving a heterogeneous fleet of multi-compartment vehicles servicing a set of orders of different fuels. Two new features are introduced that affect significantly the performance of the fuel distribution process in terms of safety and efficiency: (i) loading trucks so that the payload remains balanced throughout each phase of a delivery route, and (ii) sequencing the requests for loading trucks at the depot loading facilities. A Mixed Integer Programming formulation is presented and an Adaptive Large Neighbourhood Search algorithm with various novel features is developed and benchmarked. A new loading model is formed and solved for allocating the ordered items (fuel) to vehicle compartments, as part of constructing/repairing delivery routes. The computational performance of the proposed solution approach has been tested on a series of benchmark problems. Moreover, a series of experiments were performed in order to assess the effect of the balanced loading constraints on the traveled distance. The results indicate that the effect of this type of constraint on the total traveled distance is kept at a reasonable level, reaching a maximum increase of 4.37%. The computational tools presented in this work may accommodate the dispatchers’ work in producing efficient and safe delivery routes while managing efficiently any potential bottleneck in the truck loading facilities.

Keywords: Hazardous materials; Vehicle routing; Loading constraints; Sequencing; Adaptive Large Neighbourhood Search; Multiple compartments (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-023-05752-1

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