MMEA is compared with three other methods, KP1, Omni-Optimizer and RM-MEDA, on a set of test instances, five of which are proposed in this paper. The experimental results clearly suggest that, overall, MMEA performs significantly better than the three compared algorithms in approximating both ...
Mixed Best Members Based Optimizer for Solving Various Optimization Problems Numerous designed optimization problems in different disciplines of science should be solved using appropriate techniques. population based optimization al... Doumari, Sajjad Amiri,Zeidabadi, Fatemeh Ahmadi,Dehghani, Mohammad,... ...
C. (1998). A modified particle swarm optimizer. In Proceedings of the IEEE international conference on evolutionary computation (pp. 69–73). Piscataway: IEEE Press. Google Scholar Shi, Y., & Eberhart, R. C. (2001). Fuzzy adaptive particle swarm optimization. In Proceedings of the IEEE...
来自 Semantic Scholar 喜欢 0 阅读量: 100 作者:M Spiliopoulou,M Hatzopoulos 摘要: Proposes a parallel optimizer for queries containing a large number of joins, as well as set operators and aggregate functions. The platform for the execution is a shared-disk multiprocessor machine supporting bushy...
🐛 Describe the bug To avoid CPU OOMs, our training library only loads monolithic checkpoints on rank 0 and broadcasts to all other ranks (as PyTorch checkpointing supports). When migrating to the new distributed APIs, set_optimizer_state...
~\AppData\Roaming\Python\Python37\site-packages\paddle\optimizer\optimizer.py in _add_accumulator(self, name, param, dtype, fill_value, shape, type, device)513 if len(self._accumulators_holder) > 0:514 assert var_name in self._accumulators_holder, \--> 515 "Optimizer set error, {} sho...
A general-purpose global optimizer: Implimentation and applications This paper, written from a user stand-point, advocates the Adaptive Random Search strategy as an efficient tool for global optimization. First is presented... VJF Lebruchec - 《Mathematics & Computers in Simulation》 被引量: 124...
OptimizeRasters is a set of tools for accomplishing three tasks: converting raster data to optimized file formats, moving data to cloud storage, and creating raster proxies. The result is more efficient, scalable, and elastic data access with a lower storage cost.Converting...
hive.cbo.costmodel.local.fs.write是 Hive 中的一个配置属性,用于指定是否启用 Cost-Based Optimizer(CBO)中关于本地文件系统(Local FS)写操作成本的计算模型。CBO 是一个优化器,它使用成本模型来选择执行计划,以提高查询性能。 在Hive 配置中,可以使用以下方式设置hive.cbo.costmodel.local.fs.write: ...
2021 Elsevier B.V.In this paper, we enriched Ant Colony Optimization (ACO) with interval outranking to develop a novel multi-objective ACO optimizer to app... G Rivera,CCA Coello,L Cruz-Reyes,... - 《Swarm & Evolutionary Computation》 被引量: 0发表: 2022年 Advantages of metaheuristics fo...