10,430 research outputs found

    Enhanced genetic algorithm-based fuzzy multiobjective strategy to multiproduct batch plant design

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    This paper addresses the problem of the optimal design of batch plants with imprecise demands in product amounts. The design of such plants necessary involves how equipment may be utilized, which means that plant scheduling and production must constitute a basic part of the design problem. Rather than resorting to a traditional probabilistic approach for modeling the imprecision on product demands, this work proposes an alternative treatment by using fuzzy concepts. The design problem is tackled by introducing a new approach based on a multiobjective genetic algorithm, combined wit the fuzzy set theory for computing the objectives as fuzzy quantities. The problem takes into account simultaneous maximization of the fuzzy net present value and of two other performance criteria, i.e. the production delay/advance and a flexibility index. The delay/advance objective is computed by comparing the fuzzy production time for the products to a given fuzzy time horizon, and the flexibility index represents the additional fuzzy production that the plant would be able to produce. The multiobjective optimization provides the Pareto's front which is a set of scenarios that are helpful for guiding the decision's maker in its final choices. About the solution procedure, a genetic algorithm was implemented since it is particularly well-suited to take into account the arithmetic of fuzzy numbers. Furthermore because a genetic algorithm is working on populations of potential solutions, this type of procedure is well adapted for multiobjective optimization

    An artificial immune system for fuzzy-rule induction in data mining

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    This work proposes a classification-rule discovery algorithm integrating artificial immune systems and fuzzy systems. The algorithm consists of two parts: a sequential covering procedure and a rule evolution procedure. Each antibody (candidate solution) corresponds to a classification rule. The classification of new examples (antigens) considers not only the fitness of a fuzzy rule based on the entire training set, but also the affinity between the rule and the new example. This affinity must be greater than a threshold in order for the fuzzy rule to be activated, and it is proposed an adaptive procedure for computing this threshold for each rule. This paper reports results for the proposed algorithm in several data sets. Results are analyzed with respect to both predictive accuracy and rule set simplicity, and are compared with C4.5rules, a very popular data mining algorithm

    Genetic algorithms

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    Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology

    GENERALISED OPTIMAL STOPPING STRATEGIES WITH APPLICATIONS TO FINANCE

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    In this paper we examine the problem of determining the best time to sell an asset, where the stock price is modelled by a hybrid process. In this paper hybrid variable is a mathematical concept that is used to describe a situation in which randomness and fuzziness simultaneously appear in a system or phenomenon. Based on this concept, a hybrid stopping time problem is formulated and investigated. A verification theorem is derived and proved. We illustrate the application of the verification theorem through a practical example in mathematics of finance. A power function with exponent , is used as the utility function in the example. This study is extending the model from Oksendal [12] by including the fuzzy component since market value of assets is usually described using vague human language. The theory of hybrid variables provides a more realistic description of the evolution of price processes of financial assets. Keywords: Randomness, fuzziness, Fuzzy variable, fuzzy process, hybrid variable, hybrid process, stopping time
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