A new approach to fitness improvement in multi-correlated binary response model

Reza Kamranrad, Mehdi Koosha and Majid Jalili

International Journal of Productivity and Quality Management, 2016, vol. 18, issue 4, 499-517

Abstract: The main purpose of this manuscript is to improve the concordance of multi-correlated binary response problems using heuristic and meta-heuristic methods. For this purpose and modelling the problem, the log-linear model parameters should be estimated. In this research, an iterative nonlinear heuristic method has been proposed for simultaneous parameter estimation of multi-binary response problem. The fitness analysis of the mentioned method is evaluated by comparing the results with their counterparts in the case of independency between responses by three numerical examples in various sizes. Results illustrate the fact that the proposed heuristic method performs well in comparison with the separate estimation of the coefficients with respect to number of concordances criterion. Then, a meta-heuristic approach called simulated annealing (SA) is applied to develop the model's fitness in which the best set of controllable variables is determined in order to maximise the number of concordances.

Keywords: model fitness; log-linear modelling; correlated binary responses; metaheuristics; multi-correlated binary response models; simulated annealing. (search for similar items in EconPapers)
Date: 2016
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