this paper considers the job scheduling problem in virtual manufacturing cells (vmcs) with the goal of minimizing two objectives namely, makespan and total travelling distance. to solve this problem two algorithms are proposed: traditional non-dominated sorting genetic algorithm (nsga-ii) and knowledge-based non-dominated sorting genetic algorithm (kbnsga-ii). the difference between these algor...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

quantitative structure-activity relationship (qsar) models were employed for prediction the activity of p2x7 receptor antagonists. a data set consisted of 50 purine derivatives was utilized in the model construction where 40 and 10 of these compounds were in the training and test sets respectively. a suitable group of calculated molecular descriptors was selected by employing stepwise multiple ...

typographical data entry errors and incomplete documents, produce imperfect records in real world databases. these errors generate distinct records which belong to the same entity. the aim of approximate record matching is to find multiple records which belong to an entity. in this paper, an algorithm for approximate record matching is proposed that can be adapted automatically with input error...

 In this paper, utilization of clustering algorithms for data fusion in decision level is proposed. The results of automatic isolated word recognition, which are derived from speech spectrograph and Linear Predictive Coding (LPC) analysis, are combined with each other by using fuzzy clustering algorithms, especially fuzzy k-means and fuzzy vector quantization. Experimental results show that the...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

A new version of Genetic Algorithms, the Breeder Genetic Algorithms, has been recently proposed in literature and successfully applied to the continuous parameter optimisation. In this paper we aim to test this technique against a classical discrete Genetic Algorithm on a typical optimisation problem in Aerodynamics, the problem of determining the coordinates of an airfoil given a surface press...

This is a shorter version of an article presented in: Fundamenta Informaticae, vol. 28 (3, 4), pp: 423-430. IOS Press, 1996. A lot of research on genetic algorithms theory is concentrated on classical, binary case. However, there are many other types of useful genetic algorithms (GA), e.g. tree-based (genetic programming), or order-based ones. This paper shows, that many of classical results ca...