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Genetic-fuzzy mining (GFM) was proposed to train fuzzy membership functions, thus enhancing the final solution quality. However, it is quite time-consuming because of frequent database scans for fitness evaluation. In this paper, we propose a parallel algorithm with MapReduce architecture to further speed up the genetic-fuzzy mining process. In the proposed approach, the master processor randomly...
In this paper, to increase the diversity of stock portfolios, the diverse group stock portfolio mining algorithm is proposed based on the grouping genetic algorithm. Each chromosome is represented by grouping part, stock part and stock portfolio part. The fitness function that consists of portfolio satisfaction, group balance and diversity factor is designed to evaluate quality of chromosomes. The...
In this paper, a grouping genetic algorithm based approach is proposed for dividing stocks into groups and mining a set of stock portfolios, namely group stock portfolio. Each chromosome consists of three parts. Grouping and stock parts are used to indicate how to divide stocks into groups. Stock portfolio part is used to represent the purchased stocks and their purchased units. The fitness of each...
Since various objective functions should be considered for optimizing the portfolio, this study proposes a multi-objective genetic portfolio optimization approach with user's requests for deriving Pareto solutions. The two objective functions used in this study are return on investment and suitability of a portfolio. The suitability of a chromosome consists of a portfolio penalty and an investment...
In this paper, we discuss the scheduling problem of assigning jobs on multiple parallel machines with mold constraints. The mold constraint specifies that each job needs to be processed with specific molds on a machine and there is an arbitrary amount for each type of molds. Besides, different machines can mount different molds. Setup time is also considered when a first job in a machine starts or...
In this paper, a type-2 genetic-fuzzy mining algorithm is proposed for mining a set of type-2 membership functions for mining fuzzy association rules. It first encodes the type-2 membership functions of each item into a chromosome. The quantitative transactions are then transformed into fuzzy values according to the type-2 membership functions. Each chromosome is then evaluated by the number of large...
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