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Sophie N. Parragh

Bio: Sophie N. Parragh is an academic researcher from Johannes Kepler University of Linz. The author has contributed to research in topics: Vehicle routing problem & Heuristic (computer science). The author has an hindex of 20, co-authored 43 publications receiving 2653 citations. Previous affiliations of Sophie N. Parragh include University of Vienna & Vienna University of Economics and Business.

Papers
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Journal ArticleDOI
01 Jun 2008
TL;DR: Single as well as multi vehicle mathematical problem formulations for all three VRPPD types are given, and the respective exact, heuristic, and metaheuristic solution methods are discussed.
Abstract: This paper is the second part of a comprehensive survey on pickup and delivery models. Basically, two problem classes can be distinguished. The first part dealt with the transportation of goods from the depot to linehaul customers and from backhaul customers to the depot. In this class four subtypes were considered, namely the Vehicle Routing Problem with Clustered Backhauls (VRPCB all linehauls before backhauls), the Vehicle Routing Problem with Mixed linehauls and Backhauls (VRPMB any sequence of linehauls and backhauls permitted), the Vehicle Routing Problem with Divisible Delivery and Pickup (VRPDDP customers demanding delivery and pickup service can be visited twice), and the Vehicle Routing Problem with Simultaneous Delivery and Pickup (VRPSDP customers demanding both services have to be visited exactly once). The second part now considers all those problems where goods are transported between pickup and delivery locations, denoted as Vehicle Routing Problems with Pickups and Deliveries (VRPPD). These are the Pickup and Delivery VRP (PDVRP unpaired pickup and delivery points), the classical Pickup and Delivery Problem (PDP paired pickup and delivery points), and the Dial-A-Ride Problem (DARP paired pickup and delivery points and user inconvenience taken into consideration). A single as well as a multi vehicle mathematical problem formulation for all three VRPPD types is given, and the respective exact, heuristic, and metaheuristic solution methods are discussed.

703 citations

Journal ArticleDOI
13 Mar 2008
TL;DR: This paper is the first part of a comprehensive survey on pickup and delivery problems and the corresponding exact, heuristic, and metaheuristic solution methods are discussed.
Abstract: This paper is the first part of a comprehensive survey on pickup and delivery problems. Basically, two problem classes can be distinguished. The first class, discussed in this paper, deals with the transportation of goods from the depot to linehaul customers and from backhaul customers to the depot. This class is denoted as Vehicle Routing Problems with Backhauls (VRPB). Four subtypes can be considered, namely the Vehicle Routing Problem with Clustered Backhauls (VRPCB – all linehauls before backhauls), the Vehicle Routing Problem with Mixed linehauls and Backhauls (VRPMB – any sequence of linehauls and backhauls permitted), the Vehicle Routing Problem with Divisible Delivery and Pickup (VRPDDP – customers demanding delivery and pickup service can be visited twice), and the Vehicle Routing Problem with Simultaneous Delivery and Pickup (VRPSDP – customers demanding both services have to be visited exactly once). The second class, dealt with in the second part of this survey, refers to all those problems where goods are transported between pickup and delivery locations. These are the Pickup and Delivery Vehicle Routing Problem (PDVRP – unpaired pickup and delivery points), the classical Pickup and Delivery Problem (PDP – paired pickup and delivery points), and the Dial-A-Ride Problem (DARP – passenger transportation between paired pickup and delivery points and user inconvenience taken into consideration). Single as well as multi vehicle versions of the mathematical problem formulations are given for all four VRPB types, the corresponding exact, heuristic, and metaheuristic solution methods are discussed.

624 citations

Journal ArticleDOI
TL;DR: This paper proposes a competitive variable neighborhood search-based heuristic, using three classes of neighborhoods, based on the ejection chain idea, which exploits the existence of arcs where the vehicle load is zero, giving rise to natural sequences of requests.

202 citations

Journal ArticleDOI
TL;DR: A metaheuristic algorithm, embedding a large neighborhood search heuristic in a multi-directional local search framework, is proposed to solve the home care routing and scheduling problem as a bi-objective problem.

193 citations

Journal ArticleDOI
TL;DR: The service technician routing and scheduling problem with and without team building is defined and high quality solutions are obtained within short computation times by means of an adaptive large neighborhood search algorithm.
Abstract: Motivated by the problem situation faced by infrastructure service and maintenance providers, we define the service technician routing and scheduling problem with and without team building: a given number of technicians have to complete a given number of service tasks. Each technician disposes of a number of skills at different levels and each task demands technicians that provide the appropriate skills of at least the demanded levels. Time windows at the different service sites have to be respected. In the case where a given task cannot be serviced by any of the technicians, outsourcing costs occur. In addition, in some companies technicians have to be grouped into teams at the beginning of the day since most of the tasks cannot be completed by a single technician. The objective is to minimize the sum of the total routing and outsourcing costs. We solve both problem versions by means of an adaptive large neighborhood search algorithm. It is tested on both artificial and real-world instances; high quality solutions are obtained within short computation times.

161 citations


Cited by
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Journal ArticleDOI

1,549 citations

Book ChapterDOI
Eric V. Denardo1
01 Jan 2011
TL;DR: This chapter sees how the simplex method simplifies when it is applied to a class of optimization problems that are known as “network flow models” and finds an optimal solution that is integer-valued.
Abstract: In this chapter, you will see how the simplex method simplifies when it is applied to a class of optimization problems that are known as “network flow models.” You will also see that if a network flow model has “integer-valued data,” the simplex method finds an optimal solution that is integer-valued.

828 citations

Journal ArticleDOI
TL;DR: The purpose is to review the most up-to-date state-of-the-art of GVRP, discuss how the traditional VRP variants can interact with G VRP and offer an insight into the next wave of research into GVRp.
Abstract: Green Logistics has emerged as the new agenda item in supply chain management. The traditional objective of distribution management has been upgraded to minimizing system-wide costs related to economic and environmental issues. Reflecting the environmental sensitivity of vehicle routing problems (VRP), an extensive literature review of Green Vehicle Routing Problems (GVRP) is presented. We provide a classification of GVRP that categorizes GVRP into Green-VRP, Pollution Routing Problem, VRP in Reverse Logistics, and suggest research gaps between its state and richer models describing the complexity in real-world cases. The purpose is to review the most up-to-date state-of-the-art of GVRP, discuss how the traditional VRP variants can interact with GVRP and offer an insight into the next wave of research into GVRP. It is hoped that OR/MS researchers together with logistics practitioners can be inspired and cooperate to contribute to a sustainable industry.

741 citations

Journal ArticleDOI
01 Jun 2008
TL;DR: Single as well as multi vehicle mathematical problem formulations for all three VRPPD types are given, and the respective exact, heuristic, and metaheuristic solution methods are discussed.
Abstract: This paper is the second part of a comprehensive survey on pickup and delivery models. Basically, two problem classes can be distinguished. The first part dealt with the transportation of goods from the depot to linehaul customers and from backhaul customers to the depot. In this class four subtypes were considered, namely the Vehicle Routing Problem with Clustered Backhauls (VRPCB all linehauls before backhauls), the Vehicle Routing Problem with Mixed linehauls and Backhauls (VRPMB any sequence of linehauls and backhauls permitted), the Vehicle Routing Problem with Divisible Delivery and Pickup (VRPDDP customers demanding delivery and pickup service can be visited twice), and the Vehicle Routing Problem with Simultaneous Delivery and Pickup (VRPSDP customers demanding both services have to be visited exactly once). The second part now considers all those problems where goods are transported between pickup and delivery locations, denoted as Vehicle Routing Problems with Pickups and Deliveries (VRPPD). These are the Pickup and Delivery VRP (PDVRP unpaired pickup and delivery points), the classical Pickup and Delivery Problem (PDP paired pickup and delivery points), and the Dial-A-Ride Problem (DARP paired pickup and delivery points and user inconvenience taken into consideration). A single as well as a multi vehicle mathematical problem formulation for all three VRPPD types is given, and the respective exact, heuristic, and metaheuristic solution methods are discussed.

703 citations