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Addressing Dependent Data in Constrained Optimization Problems: A WOA-based Algorithm | ||
International Journal of Industrial Electronics Control and Optimization | ||
مقاله 4، دوره 7، شماره 2، مرداد 2024، صفحه 119-127 اصل مقاله (579.64 K) | ||
نوع مقاله: Research Articles | ||
شناسه دیجیتال (DOI): 10.22111/ieco.2024.47541.1523 | ||
نویسندگان | ||
Asieh Ghanbarpour* 1؛ Soheil Zaremotlagh2؛ Fahimeh Dabaghi-Zarandi3 | ||
1Faculty of Electrical and Computer Engineering, University of Sistan and Baluchestan, Zahedan, Iran. | ||
2Department of Mining Engineering, Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran. | ||
3Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran. | ||
چکیده | ||
Optimization algorithms are widely used in various fields to find the best solution to a problem by minimizing or maximizing an objective function, subject to certain constraints. This paper introduces the development and application of an innovative optimization algorithm (WOADD) designed to address the challenges posed by constrained optimization problems with dependent data. Unlike traditional algorithms that struggle with data dependencies and valid range constraints, WOADD incorporates a novel normalization process and a dynamic updating mechanism that accurately considers the interdependencies among features. Specifically, it adjusts the search strategy by calculating a scaling parameter to maneuver within feasible regions, ensuring the preservation of data dependencies and adherence to constraints, thus leading to more efficient and precise optimization outcomes. Our extensive experimental analysis, comparing WOADD against other swarm-based optimization methods on a suite of benchmark functions, illustrates its superior performance in terms of faster convergence rates, improved solution quality, and enhanced determinism in outcomes. | ||
کلیدواژهها | ||
Swarm-based optimization؛ Constraints؛ Compositional data؛ Penalty function | ||
مراجع | ||
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