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Генетичен алгоритъм×Хармонийно търсене×
ОбластОптимизацияОптимизация
СемействоProcess / pipelineProcess / pipeline
Година на възникване19752001
СъздателJohn Henry HollandZong Woo Geem, Joong Hoon Kim, G. V. Loganathan
ТипPopulation-based metaheuristicMetaheuristic population-based optimization
Основополагащ източникHolland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A New Heuristic Optimization Algorithm: Harmony Search. Simulation, 76(2), 60–68. DOI ↗
Други названияGA, evolutionary algorithm, Genetik Algoritma — Evrimsel OptimizasyonHS algorithm, Harmoni Araması (Harmony Search), music-inspired optimization
Свързани55
РезюмеA genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail.Harmony Search (HS) is a population-based metaheuristic optimization algorithm introduced by Geem, Kim, and Loganathan in 2001. It mimics the improvisation process of jazz musicians seeking a perfect state of harmony, using three operators — memory consideration, pitch adjustment, and random selection — to generate candidate solutions. The algorithm applies to both continuous and discrete variables and has found wide use in engineering design, water distribution network optimization, and combinatorial problems.
ScholarGateНабор от данни
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  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Genetic Algorithm · Harmony Search. Извлечено на 2026-06-17 от https://scholargate.app/bg/compare