Dynamic Initial Weight Assignment for MaxSAT
Algorithms, 2021 The Maximum Satisfiability (Maximum Satisfiability (MaxSAT)) approach is the choice, and perhaps the only one, to deal with most real-world problems as most of them are unsatisfiable.
Abdelraouf Ishtaiwi, Qasem Abu Al-Haija
doaj +1 more source
Optimal analog wavelet bases construction using hybrid optimization algorithm [PDF]
, 2016 An approach for the construction of optimal analog wavelet bases is presented. First, the definition of an analog wavelet is given. Based on the definition and the least-squares error criterion, a general framework for designing optimal analog wavelet ...
He, Yigang, Li, Hongmin, Sun, Yichuang
core +3 more sources
NILS: a Neutrality-based Iterated Local Search and its application to Flowshop Scheduling [PDF]
, 2011 This paper presents a new methodology that exploits specific characteristics from the fitness landscape. In particular, we are interested in the property of neutrality, that deals with the fact that the same fitness value is assigned to numerous ...
Dhaenens, Clarisse +4 more
core +4 more sources
Modified Biogeography-Based Optimization with Local Search Mechanism
Journal of Applied Mathematics, 2013 Biogeography-based optimization (BBO) is a new effective population optimization algorithm based on the biogeography theory with inherently insufficient exploration capability.
Quanxi Feng +5 more
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Multi-agent collaborative search : an agent-based memetic multi-objective optimization algorithm applied to space trajectory design [PDF]
, 2011 This article presents an algorithm for multi-objective optimization that blends together a number of heuristics. A population of agents combines heuristics that aim at exploring the search space both globally and in a neighbourhood of each agent.
Deb K. A. +5 more
core +2 more sources
Efficient Local Search for Pseudo Boolean Optimization
, 2021 Pseudo-Boolean Optimization (PBO) can be used to model many combinatorial optimization problems. PBO instances encoded from real-world applications are often large and difficult to solve; in many cases, close-to-optimal solutions are useful and can be found reasonably efficiently, using incomplete algorithms.
Lei, Z., Cai, S., Luo, C., Hoos, H.H.
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Heterogeneous differential evolution particle swarm optimization with local search
Complex & Intelligent Systems, 2023 To develop a high performance and widely applicable particle swarm optimization (PSO) algorithm, a heterogeneous differential evolution particle swarm optimization (HeDE-PSO) is proposed in this study.
Anping Lin +4 more
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An improved particle swarm optimization combined with double-chaos search
Mathematical Biosciences and Engineering, 2023 Particle swarm optimization (PSO) has been successfully applied to various complex optimization problems due to its simplicity and efficiency. However, the update strategy of the standard PSO algorithm is to learn from the global best particle, making it
Xuepeng Zheng +5 more
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Bayesian optimization for computationally extensive probability distributions [PDF]
, 2018 An efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique.
Hukushima, Koji, Tamura, Ryo
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Local policy search with Bayesian optimization
, 2021 Reinforcement learning (RL) aims to find an optimal policy by interaction with an environment. Consequently, learning complex behavior requires a vast number of samples, which can be prohibitive in practice. Nevertheless, instead of systematically reasoning and actively choosing informative samples, policy gradients for local search are often obtained ...
Müller, S., Rohr, A., Trimpe, S.
openaire +3 more sources