元启发式算法
48 种方法属于此方法族。
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基于智能体的蚁群优化Agent-Based Ant Colony Optimization (AB-ACO) models individual ants as autonomous agents that probabilistically construct solutions by following and depositing pheromone trails on Agent-Based Genetic AlgorithmAn Agent-Based Genetic Algorithm (ABGA) partitions a genetic algorithm's population across a network of autonomous agents, each maintaining a local sub-population and evolving it i基于智能体的NSGA-IIAgent-based NSGA-II embeds the NSGA-II evolutionary algorithm inside an agent-based simulation loop so that objective values for each candidate solution are determined by running a基于智能体的禁忌搜索Agent-Based Tabu Search (ABTS) embeds the tabu search metaheuristic inside a multi-agent framework where autonomous agents each run independent or cooperating tabu search threads, 蚁群优化Ant Colony Optimization (ACO) is a metaheuristic algorithm introduced by Marco Dorigo and colleagues in the early 1990s that solves combinatorial optimisation problems by simulatin人工蜂群（ABC）优化Artificial Bee Colony (ABC) is a population-based swarm intelligence metaheuristic introduced by Karaboga and Basturk in 2007. It models the cooperative foraging behavior of a hone
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全部方法 48
基于智能体的蚁群优化Agent-Based Genetic Algorithm基于智能体的NSGA-II基于智能体的禁忌搜索蚁群优化人工蜂群（ABC）优化蝙蝠算法贝叶斯蚁群优化贝叶斯遗传算法贝叶斯NSGA-II贝叶斯粒子群优化贝叶斯模拟退火贝叶斯禁忌搜索布谷鸟搜索确定性遗传算法确定性粒子群优化确定性模拟退火差分进化萤火虫算法遗传算法灰狼优化算法Harmony Search超启发式算法数学启发式算法：数学规划与元启发式算法的混合模因算法多目标蚁群优化 (MOACO)多目标遗传算法 (MOGA)多目标粒子群优化 (MOPSO)多目标模拟退火 (MOSA)多目标禁忌搜索 (MOTS)NSGA-IINSGA-III粒子群优化 (PSO)策略情景遗传算法政策情景粒子群优化鲁棒蚁群优化稳健遗传算法Robust NSGA-II鲁棒粒子群优化鲁棒模拟退火鲁棒禁忌搜索模拟启发式算法：结合仿真与元启发式算法求解随机优化问题模拟退火随机遗传算法随机NSGA-II随机粒子群优化随机禁忌搜索禁忌搜索