Simple heuristics for the multi-period fleet size and mix vehicle routing problem

Pasha, Urooj; Hoff, Arild; Hvattum, Lars Magnus

doi:10.1080/03155986.2016.1149314

Cited by 7 publications

(15 citation statements)

References 37 publications

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“…Each retailer is assigned to a single opened DC by constraints (13) and (14). Constraints (15) state that each DC can be opened in one of the capacity levels.…”

Section: Decision Variables Y Ementioning

confidence: 99%

“…Vehicle routes of the sequential solution are found using an algorithm based on Pasha et al [15]. The significant differences between our algorithm and the referenced algorithm are explained in the relevant parts.…”

Section: Finding Vehicle Routesmentioning

confidence: 99%

mentioning

confidence: 99%

“…The f indAllRoutes method presented in Table 4 differs from the method proposed by Pasha et al [15] in steps 6-20. The most crucial difference is using four strategies consecutively in this study instead of using just one randomly generated strategy as in the Pasha et al [15]. The first three strategies are Average Plus Large Vehicle Capacity (ALVC), Average Plus Highest Frequency Fraction Vehicle Capacity (AHFFVC) and Vehicle Mix from the Largest Day (VMLD) strategies that give the first three best results as stated in Pasha et al [15].…”

mentioning

confidence: 99%

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A model and two heuristic methods for The Multi-Product Inventory-Location-Routing Problem with heterogeneous fleet

Arslan¹,

İşleyen²

2022

JIMO

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<p style='text-indent:20px;'>The Multi-Product Inventory-Location-Routing Problem with heterogeneous fleet considers a supply chain, which comprises multiple producers, potential distribution centers (DCs) with opening capacity levels and geographically scattered retailers each of which has deterministic demand over a discrete planning horizon. The goal is determining a set of DCs with their capacity levels to open, assigning retailers to the opened DCs, finding product quantities to be ordered by and distributed from opened DCs and determining the fleet and routes to satisfy the demands of retailers with minimum cost. A mixed-integer linear programming model is proposed to describe the problem, which is strengthened by two valid inequalities. Since the commercial solver can only solve the very small-sized instances within a reasonable time, two heuristic methods are developed. Results show that the proposed valid inequalities are effective and both methods provide important savings in acceptable run times compared to the commercial solver.</p>

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“…Each retailer is assigned to a single opened DC by constraints (13) and (14). Constraints (15) state that each DC can be opened in one of the capacity levels.…”

Section: Decision Variables Y Ementioning

confidence: 99%

Section: Finding Vehicle Routesmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

A model and two heuristic methods for The Multi-Product Inventory-Location-Routing Problem with heterogeneous fleet

Arslan¹,

İşleyen²

2022

JIMO

View full text Add to dashboard Cite

show abstract

“…This case corresponds to applications in which the fleet is acquired (or rented for a short term) or where the demand is stable over a long time period. Kilby and Urli (2016), Pasha et al (2016), and Bertoli et al (2019) have recently extended the FMVRP to multi-period and stochastic settings, helping to bridge the gap between the heterogeneous VRP and its tactical fleet composition applications.…”

Section: Routing and Fleet Compositionmentioning

confidence: 99%