Exact Method for the Vehicle Routing Problem with Mixed Linehaul and Backhaul Customers, Heterogeneous Fleet, time Window and Manufacturing Capacity

Oesterle, Jonathan; Bauernhansl, Thomas

doi:10.1016/j.procir.2015.12.040

Cited by 20 publications

(8 citation statements)

References 18 publications

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“…The lowest average objective values belong to the U [1,8] setting, since the highest number of orders can be loaded onto the same vehicle. The numbers of vehicles for U [1,16] and U [4,12] settings are similar. U[1,16] has a higher variance; some vehicles can carry orders of many customers while some visit only one customer, increasing the routing cost.…”

Section: Numerical Resultsmentioning

confidence: 90%

“…Since vehicles can carry many orders, an increased number of assignment combinations increases CPU times in this setting. Following the reverse reasoning, U [4,12] yields the fastest solutions. The combinatorial nature of the problem prevails as the number of customers increases, and the instances cannot be solved in reasonable times for more than 20 customers.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…This option is called lowdemand-low-variance setting. Considering demand value and distribution range, we can have two more options, high-demand-high-variance setting (U [1,16]) and high-demand-low-variance setting (U [4,12]). The fuel cost is assumed to be a=1.4 USD/km in all settings, while the fixed cost of using a vehicle is set at one of two levels, either USD 200 or USD 400.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…In the VRP, soft time windows (STW) [8] or hard time windows (HTW) [9] can be defined to determine operational constraints while servicing each node. Another operational classification identifies the problem as pickup and delivery (PD) [10], backhaul (BH) [11] or backhaul and linehaul (BH&LH) [12], as opposed to the classical linehaul problems. If the demand of a customer can be satisfied by more than one vehicle, the VRP with split delivery (SLD) [13] is valid; otherwise, no split deliveries are allowed.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Vehicle Routing with Compartments Under Product Incompatibility Constraints

Taşar

Eliiyi

Kandiller

2019

PROMET

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This study focuses on a distribution problem involving incompatible products which cannot be stored in a compartment of a vehicle. To satisfy different types of customer demand at minimum logistics cost, the products are stored in different compartments of fleet vehicles, which requires the problem to be modeled as a multiple-compartment vehicle routing problem (MCVRP). While there is an extensive literature on the vehicle routing problem (VRP) and its numerous variants, there are fewer research papers on the MCVRP. Firstly, a novel taxonomic framework for the VRP literature is proposed in this study. Secondly, new mathematical models are proposed for the basic MCVRP, together with its multiple-trip and split-delivery extensions, for obtaining exact solutions for small-size instances. Finally, heuristic algorithms are developed for larger instances of the three problem variants. To test the performance of our heuristics against optimum solutions for larger instances, a lower bounding scheme is also proposed. The results of the computational experiments are reported, indicating validity and a promising performance of an approach.

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Section: Numerical Resultsmentioning

confidence: 90%

Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Vehicle Routing with Compartments Under Product Incompatibility Constraints

Taşar

Eliiyi

Kandiller

2019

PROMET

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“…Heterogeneous Fleet Vehicle Routing Problem (HVRP) is a type of VRP in which the vehicle is characterized by different capacities and costs [8]. Previous studies on HVRP aims to minimize the logistics cost that includes the manufacturing capacity and driver work time using branch-and-bound algorithm [9].…”

Section: Literature Reviewmentioning

confidence: 99%

Product Distribution Optimization in Food SMEs with Integer Linear Programming

Widiyanti

Dachyar²

2018

MATEC Web Conf.

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Efficient product distribution is a key driver of the overall profitability of a company. The high cost of product distribution in food SMEs is caused by the absence of a proper distribution cost calculation to obtain optimal distribution decisions. This research aims to provide SMEs with a product distribution model with the lowest cost. A Heterogenous Fleet Vehicle Routing Problem (HVRP) for SMEs product distribution is modeled in the form of Integer Linear Programming and solved using branch-andbound algorithm to obtain an optimal route and vehicle assignment with the lowest cost. The result of this research is a model that can be used by SMEs to make daily product distribution decision.

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Optimizing logistics routings in a network perspective of supply and demand nodes

Lam

2019

Cent Eur J Oper Res

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Exact Method for the Vehicle Routing Problem with Mixed Linehaul and Backhaul Customers, Heterogeneous Fleet, time Window and Manufacturing Capacity

Cited by 20 publications

References 18 publications

Vehicle Routing with Compartments Under Product Incompatibility Constraints

Vehicle Routing with Compartments Under Product Incompatibility Constraints

Product Distribution Optimization in Food SMEs with Integer Linear Programming

Optimizing logistics routings in a network perspective of supply and demand nodes

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