This paper gives some insights related to the combination of exploration and exploitation behaviors. A recurrent question for firms deals with this blend of exploration and exploitation mechanisms. ...Firms are engaged in new activities like research and at the same time in more routine ones like development and production. Thus, they should find a satisfying arrangement between exploitation. But in order to do that, they should better understand their working. This paper analyzes adaptive systems through exploration and exploitation behaviors of firms. In order to better understand the temporal articulation of those behaviors, we refer to a mapping representation of search processes using NK models (Kauffman, 1993).
Aiming at the essence of epistasis and its significance in measuring genetic algorithm hardness, a theoretical analysis and a practical research are processed. Based on the analysis of the Euclidean ...normalization of epistasis variance and the extent of epistasis coefficient, which reflect the extent of epistasis of genetic algorithms, two theorems are formulated and proved. Then the experiments using some elementary functions and NK-models are carried out to verify the method. The obtained results show that the method can determine the difficult genetic algorithm hardness problems, but may misdetermine some easy ones, some times
In this study, simulation models were developed to explore the effects of decentralization and interdependence on individuals working in research groups. We conducted the study by simulating clinical ...health-services research with large repositories of data. First, we modeled the standard research process, which we called "centralized activity," in which a highly-paid researcher accomplishes all tasks. In our second model, which we called "distributed activity," tasks were performed in parallel by specialized technicians at lower wage scales. The results showed that centralized activity is slower (21.5 weeks vs. 17.7 weeks) and more expensive (69,700 final cost vs. 34,600) than distributed activity, and places too great a load on the lone researcher. We concluded that while the distributed model may initially seem more complex, it results in shorter completion times and lower overall costs.
Interdependence between genes is an important factor causing hardness in genetic algorithms (GA). Traditional methods, which are used to measure the interaction between genes, can only reflect the ...extent of epistasis between all genes in the chromosome. In this paper, we propose the definition of the fitness landscape of schemata, and perform random walks on this landscape to study the degree of interdependence between some certain gene loci in study. According to the degree of interaction between these given gene loci, we can analyze and determine building blocks of GA. We also do a lot of experiments based on NK-models, and results of empirical analysis show that this method is effective.
