High-dimensional real-parameter optimization using the differential ant-stigmergy algorithm
نویسندگان
چکیده
Purpose – The purpose of this paper is to present an algorithm for global optimization of high-dimensional real-parameter cost functions. Design/methodology/approach – This optimization algorithm, called differential ant-stigmergy algorithm (DASA), based on a stigmergy observed in colonies of real ants. Stigmergy is a method of communication in decentralized systems in which the individual parts of the system communicate with one another by modifying their local environment. Findings – The DASA outperformed the included differential evolution type algorithm in convergence on all test functions and also obtained better solutions on some test functions. Practical implications – The DASA may find applications in challenging real-life optimization problems such as maximizing the empirical area under the receiver operating characteristic curve of glycomics mass spectrometry data and minimizing the logistic leave-one-out calculation measure for the gene-selection criterion. Originality/value – The DASA is one of the first ant-colony optimization-based algorithms proposed for global optimization of the high-dimensional real-parameter problems.
منابع مشابه
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ورودعنوان ژورنال:
- Int. J. Intelligent Computing and Cybernetics
دوره 2 شماره
صفحات -
تاریخ انتشار 2009