Real-time vehicle routing: Solution concepts, algorithms and parallel computing strategies

Ghiani, Gianpaolo; Guerriero, Francesca; Laporte, Gilbert; Musmanno, Roberto

doi:10.1016/s0377-2217(02)00915-3

Cited by 271 publications

(151 citation statements)

References 31 publications

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“…Dynamic vehicle routing problems have received significant attention in the literature as witnessed by the surveys of Psaraftis (1988Psaraftis ( , 1995 and Ghiani et al (2003). An important variant of dynamic vehicle routing is the dynamic pickup and delivery problem (DPDP) which arises, for example, in the management of urban courier services.…”

Section: Review Of the Literaturementioning

confidence: 99%

Heuristics for dynamic and stochastic routing in industrial shipping

Tirado

Hvattum

Fagerholt

et al. 2013

Computers & Operations Research

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Section: Review Of the Literaturementioning

confidence: 99%

Heuristics for dynamic and stochastic routing in industrial shipping

Tirado

Hvattum

Fagerholt

et al. 2013

Computers & Operations Research

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“…More recent work is based on metaheuristics, where a sequence of static VRPs is solved [16]. A survey of different types of DVRPs and solution concepts can be found in [12]. While the basic problem is different to the FSSP, some approaches to addressing the dynamism can be applied here as well.…”

Section: Dynamic Vrpsmentioning

confidence: 99%

On the impact of real-time information on field service scheduling

Petrakis

Hass

Bichler

2012

Decision Support Systems

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Mobile phone operators need to plan and schedule field force personnel for maintenance and repair tasks on mobile phone base stations across the country on a daily basis. In this paper, we will introduce the field force scheduling problem with priorities. Motivated by the rising popularity of mobile field force management solutions, we compare online and offline heuristics as well as hybrids to solve the problem. The results help understand the benefits of dynamic scheduling based on realtime position information as compared to traditional daily offline planning.

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“…Recent surveys on dynamic VRP can be found in [19,20,28]. Tabu search [23], genetic algorithm [21], assignment, and insertion-based heuristics [17], approximate dynamic programming [31], and nearest-vehicle based heuristic [16] have been proposed to consider online requests and uncertain travel time in the dynamic VRP problem.…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, in our experiments, the backup trip candidates are generated based on distances and travel times. In order to simplify the experiments and to better compare the algorithms, we assumed that K, the number of backup trips, is such that K ∈ {2, 3,5,10,15,20,25,30,35, 40} for test cases with more than 300 remaining trips. For test cases with 100 and 300 remaining trips, K ∈ {2, 3, 5, 10} and K ∈ {2, 3, 5, 10, 15, 20}, respectively, since smaller-size problems have fewer backup vehicles.…”

Section: Experiments Configurationmentioning

confidence: 99%

The vehicle rescheduling problem: Model and algorithms

Mirchandani

Borenstein

2007

Networks

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When a vehicle on a scheduled trip breaks down, one or more vehicles need to be rescheduled to serve the customers on that trip with minimum operating and delay costs. The problem of reassigning vehicles in real-time to this cut trip as well as to other scheduled trips with given starting and ending times, is referred to as the vehicle rescheduling problem (VRSP). This paper considers modeling, algorithmic, and computational aspects of the single-depot VRSP. The paper formulates a model for this problem and develops several fast algorithms to solve it, including parallel synchronous auction algorithms. The concept of the common feasible network (CFN) is introduced to find a good set of initial "prices" for speeding up the auction algorithm. Computational experiments on randomly generated problems are described. Computational results show that, for small problems, all of the developed algorithms demonstrate very good computational performances. For large problems, parallel CFN-based auction algorithms provide the optimal solution with much smaller computation times.

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Real-time vehicle routing: Solution concepts, algorithms and parallel computing strategies

Cited by 271 publications

References 31 publications

Heuristics for dynamic and stochastic routing in industrial shipping

Heuristics for dynamic and stochastic routing in industrial shipping

On the impact of real-time information on field service scheduling

The vehicle rescheduling problem: Model and algorithms

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