Customer Selection and Profit Maximization in Vehicle Routing Problems

Aksen, Deniz; Aras, Necatı

doi:10.1007/3-540-32539-5_6

Cited by 8 publications

(3 citation statements)

References 10 publications

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“…We adapted it to the SMDVRP by complementing with the so‐called 1‐Node and 2‐Node iterative marginal cost analysis (iMCA). An earlier marginal profit‐driven version of iMCA was proposed in (Aksen and Aras, ) for solving VRPs with customer selection and profit maximization.…”

Section: Three Solution Methods For Ri‐smdvrpmentioning

confidence: 99%

The r‐interdiction selective multi‐depot vehicle routing problem

Sadati

Aksen

Aras

2019

Int Trans Operational Res

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The protection of critical facilities has been attracting increasing attention in the past two decades. Critical facilities involve physical assets such as bridges, railways, power plants, hospitals, and transportation hubs among others. In this study we introduce a bilevel optimization problem for the determination of the most critical depots in a vehicle routing context. The problem is modeled as an attacker–defender game (Stackelberg game) from the perspective of an adversary agent (the attacker) who aims to inflict maximum disruption on a routing network. We refer to this problem as the r‐interdiction selective multi‐depot vehicle routing problem (RI‐SMDVRP). The attacker is the decision maker in the upper level problem (ULP) who chooses r depots to interdict with certainty. The defender is the decision maker in the lower level problem (LLP) who optimizes the vehicle routes in the wake of the attack. The defender has to satisfy all customer demand either using the remaining depots or through outsourcing to a third party logistics service provider. The ULP is solved through exhaustive enumeration, which is viable when the cardinality of interdictions does not exceed five among nine depots. For the LLP we implement a tabu search heuristic adapted to the selective multi‐depot VRP. Our results are obtained on a set of RI‐SMDVRP instances synthetically constructed from standard MDVRP test instances.

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Section: Three Solution Methods For Ri‐smdvrpmentioning

confidence: 99%

The r‐interdiction selective multi‐depot vehicle routing problem

Sadati

Aksen

Aras

2019

Int Trans Operational Res

Self Cite

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“…Whenever the available resources are insufficient to service all customers, the problem can be modeled as a Vehicle Routing Problem with profits (VRP with profits) (Aksen and Aras, 2006;Archetti et al, 2014b). Given a set of potential customers with known profits, the aim is to determine the subset of customers to be serviced and to construct vehicle routes that optimize the given objective function and satisfy all operational constraints.…”

Section: Introductionmentioning

confidence: 99%

The Vehicle Routing Problem with Profits and consistency constraints

Stavropoulou

Repoussis

Tarantilis

2019

European Journal of Operational Research

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“…Team orienteering problem is defined by Chao, Golden, and Wasil (1996). Different variations of Team Orienteering Problem are defined by Archetti, Feillet, Hertz, and Speranza (2009), Aksen and Aras (2006), Süral and Bookbinder (2003) and Valle, Martinez, Cunha, and Mateus (2011). Jozefowiez, Semet, and Talbi (2008) and focus on combining a multi-objective approach with multi vehicle routing problems.…”

Section: Related Literaturementioning

confidence: 99%

Selective vehicle routing for a mobile blood donation system

Sahinyazan

Kara

Taner

2015

European Journal of Operational Research

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a b s t r a c tIn this study, a mobile blood collection system is designed with the primary objective of increasing blood collection levels. This design also takes into account operational costs to aim for collection of large amounts of blood at reasonable cost. Bloodmobiles perform direct tours to certain activities to collect blood, but at the end of each day, they bring the collected blood to a designated depot to prevent its spoilage. The proposed system consists of the bloodmobiles and a new vehicle called the shuttle that visits the bloodmobiles in the field on each day and transfers the collected blood to the depot. Consequently, bloodmobiles can continue their tours without having to make daily returns to the depot.We propose a mathematical model and a 2-stage IP based heuristic algorithm to determine the tours of the bloodmobiles and the shuttle, and their lengths of stay at each stop. This new problem is defined as an extension of the Selective Vehicle Routing Problem and is referred to as the SVRP with Integrated Tours. The performances of the solution methodologies are tested first on a real data set obtained from past blood donation activities of Turkish Red Crescent in Ankara, and then on a constructed data set based on GIS data of the European part of Istanbul. The Pareto set of optimum solutions is generated based on blood amounts and logistics costs, and finally a sensitivity analysis on some important design parameters is conducted.

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Customer Selection and Profit Maximization in Vehicle Routing Problems

Cited by 8 publications

References 10 publications

The r‐interdiction selective multi‐depot vehicle routing problem

The r‐interdiction selective multi‐depot vehicle routing problem

The Vehicle Routing Problem with Profits and consistency constraints

Selective vehicle routing for a mobile blood donation system

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