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1
Product assembly sequence optimization based on genetic algorithm
Published 2010“…Genetic algorithm (GA) is a search technique used in computing to find approximate solution to optimization and search problem based on the theory of natural selection. …”
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2
A filtering algorithm for efficient retrieving of DNA sequence
Published 2009“…The algorithm filtered the expected irrelevant DNA sequences in database from being computed for dynamic programming based optimal alignment process. …”
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3
An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm
Published 2015“…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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4
Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
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5
An Assembly Sequence Planning Approach with a Rule-based Multi-state Gravitational Search Algorithm
Published 2015“…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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6
Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems
Published 2021“…Metaheuristic algorithms have been widely used to solve diverse kinds of optimization problems. …”
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7
A Hybrid Ant-Wolf Algorithm to Optimize Assembly Sequence Planning Problem
Published 2017“…Purpose – This paper aims to optimize the assembly sequence planning (ASP) problem using a proposed hybrid algorithm based on Ant Colony Optimization (ACO) and Gray Wolf Optimizer (GWO). …”
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8
Sequence t-way test generation using the barnacles mating optimizer algorithm
Published 2021“…More precisely, we focus on the generation of test cases due to the ordering of inputs (or sequence) using the newly developed Barnacles Mating Optimizer (BMO) Algorithm. …”
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9
Design of DNA sequence alignment accelerated system using 2-dimensional array and custom instruction on FPGA / Nur Dalilah Ahmad Sabri
Published 2018“…Thus, this research concentrates on the optimization techniques based on Custom Instruction (CI) and Rectangular Dimensional array (2D) that proposed on Smith-Waterman (SW) algorithm. …”
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10
A guided dynamic programming approach for DNA sequence similarity search
Published 2011“…An optimal alignment process based on the dynamic programming algorithms has shown to have 0(n x m) time and space complexity. …”
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11
Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
Published 2024journal::journal article -
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Full search (FS), three step search (TSS), new three step search (NTSS), diamond search (DS) and hexagon based search (HS) are the most well known block-matching algorithm. …”
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Book Chapter -
13
Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences
Published 2021“…To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. …”
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14
Multilevel optimization for dense motion estimation
Published 2011“…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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Monograph -
15
Modelling of Assembly Sequence Planning Problem using Base Part Concept
Published 2018“…Recently, various research works have been done to optimize the ASP problem using different optimization algorithms. …”
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16
Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…Then, it started to find the best sequence of jobs for each line based on the generated population by heuristic algorithm. …”
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17
Multi-state PSO GSA for solving discrete combinatorial optimization problems
Published 2016“…As a consequence, multi-state particle swarm optimization (MSPSO) and multi-state gravitational search algorithm (MSGSA) are developed. …”
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18
Modelling of assembly sequence planning problem using base part concept
Published 2018“…Recently, various research works have been done to optimize the ASP problem using different optimization algorithms. …”
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19
A review on particle swarm optimization algorithm and its variants to human motion tracking
Published 2014“…Several approaches have been proposed in the literature using different techniques.However, conventional approaches such as stochastic particle filtering have shortcomings in computational cost, slowness of convergence, suffers from the curse of dimensionality and demand a high number of evaluations to achieve accurate results. Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space.This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. …”
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20
DNA Words Based on an Enhanced Algorithm of Multi-objective Particle Swarm Optimization in a Continuous Search Space
Published 2011“…In this paper, particle swarm optimization algorithm in a continuous search space is implemented to generate a set of DNA words. …”
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