Results 1 to 10 of about 1,417,394 (361)
Higher-Order Quantum-Inspired Genetic Algorithms [PDF]
arXiv, 2014 This paper presents a theory and an empirical evaluation of Higher-Order Quantum-Inspired Genetic Algorithms. Fundamental notions of the theory have been introduced, and a novel Order-2 Quantum-Inspired Genetic Algorithm (QIGA2) has been presented. Contrary to all QIGA algorithms which represent quantum genes as independent qubits, in higher-order ...
Kucharski, Jacek, Nowotniak, Robert
arxiv +5 more sources
A Novel Genetic Algorithm using Helper Objectives for the 0-1 Knapsack Problem [PDF]
arXiv, 2014 The 0-1 knapsack problem is a well-known combinatorial optimisation problem. Approximation algorithms have been designed for solving it and they return provably good solutions within polynomial time. On the other hand, genetic algorithms are well suited for solving the knapsack problem and they find reasonably good solutions quickly.
Dong, Hongbin, He, Feidun, He, Jun
arxiv +3 more sources
Finite State Machine Synthesis for Evolutionary Hardware [PDF]
arXiv, 2013 This article considers application of genetic algorithms for finite machine synthesis. The resulting genetic finite state machines synthesis algorithm allows for creation of machines with less number of states and within shorter time. This makes it possible to use hardware-oriented genetic finite machines synthesis algorithm in autonomous systems on ...
Bereza, Andrey +2 more
arxiv +3 more sources
Hybrid quantum search with genetic algorithm optimization [PDF]
PeerJ Computer ScienceQuantum genetic algorithms (QGA) integrate genetic programming and quantum computing to address search and optimization problems. The standard strategy of the hybrid QGA approach is to add quantum resources to classical genetic algorithms (GA), thus ...
Sebastian Mihai Ardelean, Mihai Udrescu
doaj +3 more sources
Molecular geometry optimization with a genetic algorithm [PDF]
, 1995 We present a method for reliably determining the lowest energy structure of an atomic cluster in an arbitrary model potential. The method is based on a genetic algorithm, which operates on a population of candidate structures to produce new candidates with lower energies.
B. L. Zhang +16 more
arxiv +3 more sources
Using a genetic algorithm to find molecules with good docking scores [PDF]
PeerJ Physical Chemistry, 2021 A graph-based genetic algorithm (GA) is used to identify molecules (ligands) with high absolute docking scores as estimated by the Glide software package, starting from randomly chosen molecules from the ZINC database, for four different targets ...
Casper Steinmann, Jan H. Jensen
doaj +2 more sources
An improved adaptive genetic algorithm [PDF]
SHS Web of Conferences, 2022 Genetic algorithm is a classic intelligent bionic algorithm, which is evolved according to the genetic evolution process of organisms in nature, and has strong global optimization ability.
Han Shifen, Xiao Li
doaj +1 more source
Perbandingan Fluid Genetic Algorithm dan Genetic Algorithm untuk Penjadwalan Perkuliahan
Jurnal Sisfokom, 2020 The lecture schedule is a problem that belongs to the NP-Hard problem and multi-objective problem because it has several variables that affect the preparation of the schedule and has limitations that must be met. One solution that has been found is using
Muhammad Ezar Al Rivan +1 more
doaj +1 more source
Российский технологический журнал, 2020 The genetic algorithm of clustering of analysis objects in different data domains has been offered within the hybrid concept of intelligent information technologies development aimed to support decision-making.
M. A. Anfyorov
doaj +1 more source
A Hybrid Genetic Algorithm Based on Information Entropy and Game Theory
IEEE Access, 2020 To overcome the disadvantages of traditional genetic algorithms, which easily fall to local optima, this paper proposes a hybrid genetic algorithm based on information entropy and game theory.
Li Jiacheng, Li Lei
doaj +1 more source