BARGE
发表于 2025-3-23 12:29:22
Hyperplane Elimination for Quickly Enumerating Local Optima,or finding local optima are limited to very small problem sizes. We propose a method for exploiting problem structure to skip hyperplanes that cannot contain local optima, allowing runtime to scale with the number of local optima instead of with the landscape size. We prove optimality for linear fun
Expand
发表于 2025-3-23 14:59:51
Limits to Learning in Reinforcement Learning Hyper-heuristics, experimental studies have used . reinforcement learning mechanisms, however, these are inconclusive with regard to the performance of selection hyper-heuristics with these learning mechanisms. This paper points out limitations to learning with . reinforcement learning mechanisms. Our theoretical re
产生
发表于 2025-3-23 19:16:56
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bonnet
发表于 2025-3-24 00:07:46
Particle Swarm Optimisation with Sequence-Like Indirect Representation for Web Service Composition, active research topic in the past years. The advantage of having an automated composition system is that it allows users to create new applications simply by providing the required parameters, instead of having to manually assemble the services. Existing approaches to automated composition rely on
laxative
发表于 2025-3-24 02:25:45
Particle Swarm Optimization for Multi-Objective Web Service Location Allocation,st and network latency, are considered simultaneously. In order to solve this new multi-objective problem effectively, we adopted the framework of binary Particle Swarm Optimization (PSO) due to its efficacy that has been demonstrated in many optimization problems. Specifically, we developed two PSO
HARD
发表于 2025-3-24 08:54:41
Sim-EDA: A Multipopulation Estimation of Distribution Algorithm Based on Problem Similarity,delling. The proposed approach is to tackle several similar instances of the same optimization problem at once. Each subpopulation is assigned to a different instance and a migration mechanism is used for transferring information between the subpopulations. The migration process can be performed usi
DIS
发表于 2025-3-24 13:16:11
Solving the Quadratic Assignment Problem with Cooperative Parallel Extremal Optimization,cult, for many useful instances. We address this problem using a local search technique, based on Extremal Optimization and present experimental evidence that this approach is competitive. Moreover, cooperative parallel versions of our solver improve performance so much that large and hard instances
闪光你我
发表于 2025-3-24 16:10:33
W. Hempelmann,G. Hempelmann,S. Piepenbrockcult, for many useful instances. We address this problem using a local search technique, based on Extremal Optimization and present experimental evidence that this approach is competitive. Moreover, cooperative parallel versions of our solver improve performance so much that large and hard instances can be solved quickly.
tympanometry
发表于 2025-3-24 20:34:10
Solving the Quadratic Assignment Problem with Cooperative Parallel Extremal Optimization,cult, for many useful instances. We address this problem using a local search technique, based on Extremal Optimization and present experimental evidence that this approach is competitive. Moreover, cooperative parallel versions of our solver improve performance so much that large and hard instances can be solved quickly.
抛弃的货物
发表于 2025-3-25 00:52:50
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