A Language for Combinatorial Computing

Wells, Mark B.

doi:10.1016/b978-0-08-016091-7.50005-3

Cited by 30 publications

(27 citation statements)

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“…Therefore, the performance of standard commercial packages is, at best, no better than a straightforward explicit enumeration program without LP. 7 Two variations of a search enumeration algorithm, referred to as "primal" and "dual" enumeration algorithms, either explicitly or implicitly enumerate all possible solution candidates, and are based on a "backtrack" algorithm (see, e.g., Golomb and Baumert [5], Knuth [7], Lehmer [8], Salkin [15], and Wells [18]). The primal algorithm generally finds an initial solution and then seeks improved solutions.…”

Section: A Single-constraint Integer Program and Solution Strategymentioning

confidence: 99%

Two backtrack algorithms for the radio frequency intermodulation problem

1980

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Abstract. Two or more radio signals, transmitted from a small platform (e.g., a ship, satellite, or airplane, etc.), tend to produce an intermodulation product which could distort a receive signal. The intensity of intermodulation interference due to a given intermodulation frequency is known to be closely related to the lowest order, or simply the order, of the intermodulation product which can be found by solving a single constraint integer program with variables unrestricted in sign, where coefficients of the constraint equation correspond to frequencies. Two variations of backtrack, or search enumeration, algorithms, called the primal and dual backtrack algorithms, are developed to find the order of intermodulation. Extensive computational experience with these algorithms, reflecting data from naval fleet communication scenarios and potential ramifications, are given together with another application of the dual algorithm.

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Section: A Single-constraint Integer Program and Solution Strategymentioning

confidence: 99%

Two backtrack algorithms for the radio frequency intermodulation problem

1980

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“…It is not always possible to reach this minimum, however, as was proven e.g. for the case n = 12 in (Wells, 1971) and for n = 13 in (Peczarski, 2002). (Ford Jr and Johnson, 1959) propose an algorithm called merge insertion which comes very close to the theoretical limit.…”

Section: Evaluation Of Multiple Systemsmentioning

confidence: 99%

Human evaluation of machine translation through binary system comparisons

Vilar

Leusch

Ney

et al. 2007

Proceedings of the Second Workshop on Statistical Machine Translation - StatMT '07

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We introduce a novel evaluation scheme for the human evaluation of different machine translation systems. Our method is based on direct comparison of two sentences at a time by human judges. These binary judgments are then used to decide between all possible rankings of the systems. The advantages of this new method are the lower dependency on extensive evaluation guidelines, and a tighter focus on a typical evaluation task, namely the ranking of systems. Furthermore we argue that machine translation evaluations should be regarded as statistical processes, both for human and automatic evaluation. We show how confidence ranges for state-of-the-art evaluation measures such as WER and TER can be computed accurately and efficiently without having to resort to Monte Carlo estimates. We give an example of our new evaluation scheme, as well as a comparison with classical automatic and human evaluation on data from a recent international evaluation campaign.

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“…Therefore, only the order arrivals account for stochasticity. To account for the multiple permutations corresponding to o t order arrivals, we must multiply the probability of o t orders arriving with a multinomial coefficient [15]. We obtain the following probability function for new arrivals:…”

Section: (12)mentioning

confidence: 99%

An Approximate Dynamic Programming Approach to Urban Freight Distribution with Batch Arrivals

Heeswijk

Mes

Schutten

2015

Lecture Notes in Computer Science

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Abstract. We study a dispatch problem with uncontrolled batch arrivals of LTL orders at an urban consolidation center. These arrivals reflect the delivery of goods by independent carriers. The specific order properties (e.g., destination, size, delivery window) may be highly varying in city logistics, and directly distributing an incoming batch may yield high costs. Instead, the hub operator may decide to wait for incoming batches that allow for more efficient distribution. A waiting policy is required to decide which orders to ship and which orders to hold. We model the dispatching problem as a Markov decision problem. Dynamic Programming (DP) is applied to solve toy-sized instances. To solve realistic instances, we propose an Approximate Dynamic Programming (ADP) approach. Through numerical experiments, we show that the ADP approach closely approximates the optimal values of DP for small instances, and outperforms two benchmark policies for larger instances.

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A Language for Combinatorial Computing

Cited by 30 publications

References 0 publications

Two backtrack algorithms for the radio frequency intermodulation problem

Two backtrack algorithms for the radio frequency intermodulation problem

Human evaluation of machine translation through binary system comparisons

An Approximate Dynamic Programming Approach to Urban Freight Distribution with Batch Arrivals

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