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An Evaluation of Heuristic Methods for Determining the Best Table Mix In Full-Service Restaurants
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  • Sheryl E. Kimes, Cornell University School of Hotel Administration
  • Gary Thompson, Cornell University School of Hotel Administration
Publication Date
9-1-2005
Abstract
Little research has been done on the optimal mix of supply in service businesses that maximizes revenue. Our research context is the full-service restaurant table mix problem. This problem, which is quite new to the literature, finds the optimal number of different size tables for a restaurant to maximize its value (revenue or contribution) generating potential. Specifically, we examine the effectiveness of eight heuristic techniques for the problem using two experiments. The first experiment uses data from a 240-seat full-service restaurant to evaluate all eight heuristics, while the second experiment investigates the performance of selected heuristics under a broader set of environmental factors. The results of our first experiment showed that the better of the simulated annealing heuristic variants yielded the optimal solution in seven of eight test problems, averaging within 0.1% of optimal. Our second experiment showed that the simplest of the models we investigated yielded solutions within 1% of the simulated annealing solution. Finally, we observed that altering the table mix on a daily basis increased performance by over 1% compared to maintaining the optimal weekly table mix.
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Required Publisher Statement
© Elsevier. Final version published as: Kimes, S. E., & Thomas, G. M. (2005). An evaluation of heuristic methods for determining the best table mix in full-service restaurants. Journal of Operations Management, 23(6), 599-617. doi:10.1016/j.jom.2004.07.010 Reprinted with permission. All rights reserved.

Citation Information

imes, S. E., & Thomas, G. M. (2005). An evaluation of heuristic methods for determining the best table mix in full-service restaurants [Electronic version]. Retrieved [insert date], from Cornell University, SHA School site: http://scholarship.sha.cornell.edu/articles/821