A Generalized Permanent Labelling Algorithm For The Shortest Path Problem With Time Windows

Desrochers, Martin; Soumis, François

doi:10.1080/03155986.1988.11732063

Cited by 188 publications

(177 citation statements)

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“…By exploiting dominance, shortest paths-and hence minimum reduced cost pairings-are identified without examining all paths, or pairings. For a detailed exposition of multilabel, shortest path problems, see Desrochers and Soumis (1988).…”

Section: Crew Schedulingmentioning

confidence: 99%

Applications of Operations Research in the Air Transport Industry

Barnhart

Belobaba

Odoni

2003

Transportation Science

234

121

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T his paper presents an overview of several important areas of operations research applications in the air transport industry. Specific areas covered are: the various stages of aircraft and crew schedule planning; revenue management, including overbooking and legbased and network-based seat inventory management; and the planning and operations of aviation infrastructure (airports and air traffic management). For each of these areas, the paper provides a historical perspective on OR contributions, as well as a brief summary of the state of the art. It also identifies some of the main challenges for future research.

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Section: Crew Schedulingmentioning

confidence: 99%

Applications of Operations Research in the Air Transport Industry

Barnhart

Belobaba

Odoni

2003

Transportation Science

234

121

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“…Nonetheless, like the Knapsack problem, the restricted shortest path problem can be solved in pseudo-polynomial time (Desrochers & Soumis, 1988), and thus some extension of our results to vectors of costs might still be achievable.…”

Section: Summary and Future Workmentioning

confidence: 99%

Deterministic Oversubscription Planning as Heuristic Search: Abstractions and Reformulations

Domshlak

Mirkis

2015

jair

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While in classical planning the objective is to achieve one of the equally attractive goal states at as low total action cost as possible, the objective in deterministic oversubscription planning (OSP) is to achieve an as valuable as possible subset of goals within a fixed allowance of the total action cost. Although numerous applications in various fields share the latter objective, no substantial algorithmic advances have been made in deterministic OSP. Tracing the key sources of progress in classical planning, we identify a severe lack of effective domain-independent approximations for OSP.With our focus here on optimal planning, our goal is to bridge this gap. Two classes of approximation techniques have been found especially useful in the context of optimal classical planning: those based on state-space abstractions and those based on logical landmarks for goal reachability. The question we study here is whether some similar-in-spirit, yet possibly mathematically different, approximation techniques can be developed for OSP. In the context of abstractions, we define the notion of additive abstractions for OSP, study the complexity of deriving effective abstractions from a rich space of hypotheses, and reveal some substantial, empirically relevant islands of tractability. In the context of landmarks, we show how standard goal-reachability landmarks of certain classical planning tasks can be compiled into the OSP task of interest, resulting in an equivalent OSP task with a lower cost allowance, and thus with a smaller search space. Our empirical evaluation confirms the effectiveness of the proposed techniques, and opens a wide gate for further developments in oversubscription planning.

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“…Substantial additional filtering could be added by specializing the minCost function to also consider the length variable of an SR-path variable. This would require to pre-compute the all pair shortest-distance for all the k possible lengths of the path with, for instance, labeling algorithms [3,9].…”

Section: The Maxcost Constraintmentioning

confidence: 99%

Solving Segment Routing Problems with Hybrid Constraint Programming Techniques

Hartert

Schaus

Vissicchio

et al. 2015

Lecture Notes in Computer Science

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Abstract. Segment routing is an emerging network technology that exploits the existence of several paths between a source and a destination to spread the traffic in a simple and elegant way. The major commercial network vendors already support segment routing, and several Internet actors are ready to use segment routing in their network. Unfortunately, by changing the way paths are computed, segment routing poses new optimization problems which cannot be addressed with previous research contributions. In this paper, we propose a new hybrid constraint programming framework to solve traffic engineering problems in segment routing. We introduce a new representation of path variables which can be seen as a lightweight relaxation of usual representations. We show how to define and implement fast propagators on these new variables while reducing the memory impact of classical traffic engineering models. The efficiency of our approach is confirmed by experiments on real and artificial networks of big Internet actors.

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A Generalized Permanent Labelling Algorithm For The Shortest Path Problem With Time Windows

Cited by 188 publications

References 1 publication

Applications of Operations Research in the Air Transport Industry

Applications of Operations Research in the Air Transport Industry

Deterministic Oversubscription Planning as Heuristic Search: Abstractions and Reformulations

Solving Segment Routing Problems with Hybrid Constraint Programming Techniques

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