Scheduling a Bridge Club (A Case Study in Discrete Optimization)

Elenbogen, Bruce S.; Maxim, Bruce R.

doi:10.2307/2691356

Cited by 7 publications

(6 citation statements)

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“…The solution representations for the BC problem are based in the matrix representations proposed in (Simpson, 1997) (Elenbogen and Maxim, 1992) (representation R a ) and a new representation (representation R c that fixes the group A in the initial solution in the first column of the representation proposed by (Elenbogen and Maxim, 1992).…”

Section: Simulated Annealingmentioning

confidence: 99%

“…This problem, in appearance simple, arises as a complex problem when solved by an exact approach. The Bridge Club problem and its optimal solution are defined in (Elenbogen and Maxim, 1992).…”

Section: Introductionmentioning

confidence: 99%

“…BC has been solved using several approximated approaches: greedy algorithm (Elenbogen and Maxim, 1992), partial branch & bound (Elenbogen and Maxim, 1992), steepest descent (Elenbogen and Maxim, 1992), annealed search (Elenbogen and Maxim, 1992), Kreher, et. al.…”

Section: Introductionmentioning

confidence: 99%

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PROBLEM AND ALGORITHM FINE-TUNING - A Case of Study using Bridge Club and Simulated Annealing

Rangel-Valdez

Torres-Jiménez

Bracho-Rios

et al. 2009

Proceedings of the International Joint Conference on Computational Intelligence

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Sometimes, it is difficult to cope with a good set of values for the parameters of an algorithm that solves an specific optimization problem. This work presents a methodology for fine-tuning the parameters of a Simulated Annealing (SA) algorithm solving the Bridge Club (BC) problem. The methodology uses Covering Arrays as a tool that evaluates a set of values for the parameters of the SA so that it achieves its best performance when solving BC. The results in the experiments performed show that, using this methodology, the SA reached the optimal solution of the BC problem with a relatively small number of evaluations, in comparison with other strategies that solves BC.

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Section: Simulated Annealingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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PROBLEM AND ALGORITHM FINE-TUNING - A Case of Study using Bridge Club and Simulated Annealing

Rangel-Valdez

Torres-Jiménez

Bracho-Rios

et al. 2009

Proceedings of the International Joint Conference on Computational Intelligence

View full text Add to dashboard Cite

show abstract

“…Several papers have dealt with the construction or existence of balanced incomplete block designs (BIBDs) [14] and [3], and 2-concurrence designs [5,7,9,10,11,13] as an optimization problem. Also the author of [3] used genetic algorithms (optimization method) to ®nd difference sets that were required in order to locate seating diagrams.…”

Section: Introductionmentioning

confidence: 99%

“…Our TS algorithm was able to construct many difference families. In particular, we constructed six new difference families (see [2]) which lead to an equal number of new BIBDs with parameters: (49,98,18,9,3), (61,122,20,10,3), (46,92,20,10,4), (45,90,22,11,5), (85,255,24,8,2) and (34, 85, 30, 12, 10) (see [8]). …”

Section: Introductionmentioning

confidence: 99%