A label correcting approach for solving bicriterion shortest-path problems

Skriver, Anders J.V.; Andersen, Kim Allan

doi:10.1016/s0305-0548(99)00037-4

Cited by 159 publications

(110 citation statements)

References 6 publications

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“…(Modesti et al1998) also used a linear utility function that incorporates travel time, ticket cost, and "inconvenience" of transfers. Moreover, other label setting algorithms such as (Martins 1984;Corley and Moon 1985) and label correcting algorithms such as (Skriver and Andersen, 2000) have been modified for solving the MSPP.…”

Section: Literature Reviewmentioning

confidence: 99%

An advanced GA–VNS combination for multicriteria route planning in public transit networks

Dib

Moalic

Manier

et al. 2017

Expert Systems with Applications

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Nowadays, passengers in urban public transport systems do not only seek a shorttime travel, but they also ask for optimizing other criteria such as cost and effort. Therefore, an efficient routing system should incsorporate a multiobjective analysis into its search process. Several algorithms have been proposed to optimally compute the set of nondominated journeys while going from one place to another such as the generalisation of the algorithm of Dijkstra. However, such approaches become less performant or even inapplicable when the size of the network becomes very large or when the number of criteria considered is very important. Therefore, we propose in this paper an advanced heuristic approach whereby a Genetic Algorithm (GA) is combined with a Variable Neighbourhood Search (VNS) to solve the Multicriteria Shortest Path Problem (MSPP) in multimodal networks. As transportation modes, we focus on railway, bus, tram and pedestrian. As optimization criteria, we consider travel time, monetary cost, number of transfers and the total walking time. The proposed approach is compared with the exact algorithm of Dijkstra, as well as, with a standard GA and a pure VNS. Experimental results have been assessed by solving real life itinerary problems defined on the transport network of the city of Paris and its suburbs. Results indicate that the proposed combination GA-VNS represents the best approach in terms of computational time and solutions quality for a real world routing system.

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Section: Literature Reviewmentioning

confidence: 99%

An advanced GA–VNS combination for multicriteria route planning in public transit networks

Dib

Moalic

Manier

et al. 2017

Expert Systems with Applications

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show abstract

“…In (Guerriero et al, 2009), authors have developed a model on the basis of the minimum path model introduced in (Skriver & Andersen, 2000), and accounts for the energy reserve and the link stability of mobile nodes.…”

Section: Bicriteria Modelmentioning

confidence: 99%

Mathematic Models for Quality of Service Purposes in Ad Hoc Networks

Amine¹

2011

Mobile Ad-Hoc Networks: Protocol Design

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“…The second section discusses the application of evolutionary computational methods to various types of routing problems. Skriver and Andersen (2000) employ a label correcting approach to a bicriterion SPP. Their algorithm stores only label-sets and Pareto paths are recovered at the termination of the algorithm but appears to be limited to relatively small networks.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Generating P GLOBAL is NP-Hard (Gandibleux et al, 2004) and generating P GLOBAL is exponential in the worst-case (Skriver and Andersen, 2000). Given these discouraging aspects of the problem we decided that an interesting measure of quality would be to analyse the frequency which the EA evolved P approx 5P true .…”

Section: Assessing the Quality Of The Ea Approachmentioning

confidence: 99%

“…Messac and Mattson (2002) state that 'requiring a DM to manually compare more than ten solutions is never desirable'. In other cases, Skriver and Andersen (2000) remark, the DM might be satisfied with only the set of extreme efficient paths (D paths for any D>2). The experimentation does not look at very large networks because our approach to generation of consistent P true becomes burdensome and time-consuming.…”

Section: Assessing the Quality Of The Ea Approachmentioning

confidence: 99%

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An evolutionary algorithm for multicriteria path optimization problems

Mooney

Winstanley

2006

International Journal of Geographical Information Science

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For many years researchers and decision makers (DMs) faced with multicriteria shortest path problems (MSPPs) have resorted to reductions to the classical shortest path problem (SPP) by means of weighted linear combinations of the criteria. Algorithmic and approximation schemes are available to solve MSPPs but these approaches often display complexities prohibitive to their implementation on real-world applications. This paper describes the development of an Evolutionary Algorithm (EA) approach to MSPPs on networks with multiple independent criteria. The EA approach is shown to sufficiently explore the underlying network space, generate large candidate path sets, and evolve high quality approximations to the optimal MSPP solution(s). Opportunities for early termination of the EA in time-critical applications are also offered. Among the issues for further work is the integration of the EA as a tool within a GIS for path optimization.

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A label correcting approach for solving bicriterion shortest-path problems

Cited by 159 publications

References 6 publications

An advanced GA–VNS combination for multicriteria route planning in public transit networks

An advanced GA–VNS combination for multicriteria route planning in public transit networks

Mathematic Models for Quality of Service Purposes in Ad Hoc Networks

An evolutionary algorithm for multicriteria path optimization problems

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