Search Results - (( exploring sequence optimization algorithm ) OR ( java location based algorithm ))
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Assessment of integrated assembly sequence planning and line balancing optimization using metaheuristic algorithms
Published 2024“…These algorithms include Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). …”
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Conference or Workshop Item -
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Efficient Entropy-Based Decoding Algorithms For Higher-Order Hidden Markov Model
Published 2019“…State sequence for HHMM is invisible but the classical Viterbi algorithm is able to track the optimal state sequence. …”
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Thesis -
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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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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. Addressing these aforementioned issues and complementing the existing sequence based strategies such as t-SEQ, Sequence Covering Array Generator and Bee Algorithm, this thesis presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA). …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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Indexed Article -
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T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm
Published 2019“…In order to reduce test cases several T-way sequence input interaction strategies are explored, such as, Bee Algorithm(BA), Kuhn encoding (K) , ASP with Clasp , CP with Sugar, Erdem (ER) exact encoding, Tarui (TA) Method, U, UR, D and DR, Brain (BR). …”
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Conference or Workshop Item -
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Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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Design and analysis of DNA sequence alignment module using Smith-Waterman scoring patterns / Wan Abdul Qayyum Moh Salleh
Published 2013“…The system optimizes the aligning DNA fragment using Smith-Waterman algorithm with a pattern recognition algorithm. …”
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Student Project -
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Design and analysis of DNA sequence alignment module using Smith-Waterman scoring pattern: article / Wan Abdul Qayyum Moh Salleh and A.K. Halim
Published 2013“…The system optimizes the aligning DNA fragment using Smith-Waterman algorithm with a pattern recognition algorithm. …”
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Article -
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…From an application perspective, the UHDS8 algorithm efficiently captured the motion vectors in many video sequences. …”
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Book Chapter -
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Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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Article -
14
Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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Group formation using genetic algorithm
Published 2009“…However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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Monograph -
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Multi-floor indoor location estimation system based on wireless local area network
Published 2007“…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. Estimated location is reported as physical location and symbolic location. …”
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Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization
Published 2019“…Besides that, MODPSO coefficient tuning was also conducted to identify the best setting so as to optimize the problem. The results from this experiment indicated that the MODPSO algorithm presents a significant improvement in term of solution quality toward Pareto optimal and demonstrates the ability to explore the extreme solutions in the mixed-model assembly optimization search space. …”
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Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…A test suite of twelve 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 problem were solved using the proposed algorithm. …”
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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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