Search Results - (( java optimization method algorithm ) OR ( parameter adoption case algorithm ))
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1
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Addressing this issue, this paper proposes the adoption of parameter free optimization algorithms as the basis of future t-way strategies. …”
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2
Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
3
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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Thesis -
6
Optimize class time tabling by using genetic algorithm technique in UTHM
Published 2019“…This research used genetic algorithm (GA) that was applied to java programming languages with a goal of reducing conflict and optimizing the fitness. …”
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Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite
Published 2025“…This study proposes a combinatorial testing method utilizing the Whale Optimization Algorithm (WOA). …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Thesis -
9
Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria
Published 2021“…Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. …”
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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…Although useful, all aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. In the case of reactive systems, such an assumption is invalid as some parameter operations, or events, occur in sequence and hence, creating a possibility of bugs or faults triggered by the order, or sequence, of input parameters. …”
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Thesis -
11
Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…Metaheuristic algorithms have been used successfully for solving different optimization problems. …”
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Conference or Workshop Item -
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One Parameter at a time Combinatorial Testing Strategy Based on Harmony Search Algorithm OPAT-HS
Published 2018“…Even though there are some existing optimization algorithm based combinatorial testing strategies, that minimize the number of test cases, but most of these strategies based on one-test-at-a-time (OTAT) approach and none of them has adopted the one-parameter-at-a-time (OPAT) approach. …”
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Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria
Published 2021“…Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. …”
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Article -
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An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite
Published 2018“…Although useful, most of the aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. In the case of reactive system, such an assumption is invalid as some parameter operations (or events) occur in sequence and hence, creating a possibility of bugs triggered by the order (or sequence) of input parameters. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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Thesis -
16
Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting
Published 2024“…However, among the adopted MHAs, not all are compatible with optimizing the ANN for streamflow forecasting, thus requiring a thorough study as performance varies from case to case. …”
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Assessing the chaotic map population initializations for sine cosine algorithm using the case study of pairwise test suite generation
Published 2022“…The main strength of SCA is its simplicity and straightforward implementation as well as provides no parameter control adjustment. For these reasons, SCA can be adopted in many optimization problems quickly and without much tuning. …”
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Conference or Workshop Item -
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Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-way Testing
Published 2022“…This research paper outlines hundred and ten (110) outstanding nature-inspired metaheuristic algorithms for the last decades (2001 and 2021) such as Coronavirus Optimization Algorithm, Ebola Optimization Algorithm, Harmony Search, Tiki-Taka Algorithm, and so on. …”
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Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems
Published 2018“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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Thesis -
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Combinatorial test suites generation strategy utilizing the whale optimization algorithm
Published 2020“…To address this issue, combinatorial t-way testing (where t indicates the interaction strength, i.e. the number of interacting parameters (input)) was adopted to minimize the number of cases for testing. …”
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