Search Results - (( sequence optimization search algorithm ) OR ( simulation optimization using algorithm ))
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A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…However, these extensions may result in increased execution times for the algorithm. In this research, a new combinatorial algorithm named discrete simulated Kalman filter optimizer (DSKFO) is proposed to solve combinatorial optimization problem. …”
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Gravitational Search Algorithm for Assembly Sequence Planning
Published 2014“…In past few years, many optimization techniques have been used to solve the assembly sequence planning problem include Simulated Annealing (SA), Genetic Algorithm (GA), and binary Particle Swarm Optimization (BPSO). …”
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Multi-state PSO GSA for solving discrete combinatorial optimization problems
Published 2016“…These four algorithms can be used to solve discrete combinatorial optimization problems (COPs). …”
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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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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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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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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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Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.…”
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An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem
Published 2022“…A test suite of twelve optimization benchmark test functions and three global optimization problems (Team Formation Optimization - TFO, Low Autocorrelation Binary Sequence - LABS, and Modified Condition/Decision Coverage - MC/DC test case generation) were solved using the proposed algorithm. …”
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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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Solving assembly sequence planning using angle modulated simulated kalman filter
Published 2018“…This paper presents an implementation of Simulated Kalman Filter (SKF) algorithm for optimizing an Assembly Sequence Planning (ASP) problem. …”
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Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…There were also attempts to hybridize SKF with other famous algorithms such as Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Sine Cosine Algorithm (SCA) to improve its performance. …”
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Potential of data minimization techniques approach in improving DNA sequences alignment and comparison / Syed Abdul Mutalib Al Junid … [et al.]
Published 2012“…This study will initially involve algorithm modification, mathematical formulation, logic design and simulation for data minimization and existing DNA sequences alignment algorithm. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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Iteration strategy and ts effect towards the performance of population based metaheuristics
Published 2020“…This is an important issue to be considered when designing a new population-based metaheuristic. Three parent algorithms, namely, particle swarm optimization (PSO), gravitational search algorithm (GSA), and simulated Kalman filter (SKF) are used in this work to find a general pattern of the effect of iteration strategy towards the performance of population-based algorithms. …”
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Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran
Published 2018“…The proposed network reconfiguration also considered load profiles, DG output generation, DG types, and DG operating mode to decrease the total daily power loss. The chosen optimization techniques in this work include evolutionary programming (EP), particle swarm optimization (PSO), gravitational Search Algorithm (GSA), and firefly algorithm (FA). …”
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Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms : A review
Published 2023“…This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. The research articles published between 2020 and 2023 on machine learning and constraintbased modeling have been collected, synthesized, and analyzed. …”
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