雪上轻舟飞过 发表于 2025-3-27 00:17:54
tions of other non-terminals, thereby increasing locality. The performance of the new representation is accessed on a set of benchmark problems. The results obtained confirm the effectiveness of the proposed approach, as it is able to outperform standard grammatical evolution on all selected optimization problems.outskirts 发表于 2025-3-27 03:32:30
http://reply.papertrans.cn/17/1621/162027/162027_32.pngLymphocyte 发表于 2025-3-27 08:30:30
Approaches for Many-Objective Optimization: Analysis and Comparison on MNK-Landscapes,landscapes to trace the dynamics of the algorithms generating high-resolution approximations of the Pareto optimal set. Also, we use large MNK-landscapes to analyze their scalability to larger search spaces.Infirm 发表于 2025-3-27 12:56:05
Quasi-random Numbers Improve the CMA-ES on the BBOB Testbed,ts provide a significant improvement in evolutionary optimization. In this paper, we experiment quasi-random mutations on a well known test case, namely the Coco/Bbob test case. We also include experiments on translated or rescaled versions of BBOB, on which we get similar improvements.alcohol-abuse 发表于 2025-3-27 15:50:22
http://reply.papertrans.cn/17/1621/162027/162027_35.pnggeometrician 发表于 2025-3-27 17:58:58
A Distributed Hybrid Algorithm for the Graph Coloring Problem,ypes of perturbation moves are performed. All these search components are managed by a multi-agent model which uses reinforcement learning for decision making. The performance of the proposed algorithm is evaluated on well-known DIMACS benchmark instances.Indigence 发表于 2025-3-27 22:29:08
Traffic Signal Optimization: Minimizing Travel Time and Fuel Consumption,the nature and the extent of the conflict between these objectives. We also compare with a single-objective optimization algorithm where only travel time is optimized and evaluate the impact of the signals settings on gas emissions.Eulogy 发表于 2025-3-28 02:56:13
How to Mislead an Evolutionary Algorithm Using Global Sensitivity Analysis,y exploiting information gathered from GSA might not be so straightforward. In this paper, we present three mono- and multi-objective counterexamples to prove how naively combining GSA and EA may mislead an optimisation process.Formidable 发表于 2025-3-28 08:21:54
http://reply.papertrans.cn/17/1621/162027/162027_39.pnggorgeous 发表于 2025-3-28 12:24:01
0302-9743 nd Modeling,Implementations, Application of Evolutionary Paradigms to the Real World,Dynamic Optimization, Machine Learning and hybridization with other softcomputing techniques..978-3-319-31470-9978-3-319-31471-6Series ISSN 0302-9743 Series E-ISSN 1611-3349