Adaptive League Championship Algorithm (ALCA) for Independent Task Scheduling in Cloud Computing

Gade, Anup; Mundukur, Nirupama Bhat; Thakare, Nita

doi:10.18280/isi.240316

Cited by 7 publications

(1 citation statement)

References 16 publications

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“…In the recovery time, each team organizes a new change in the playing style (a new solution) for the next week match and the championship will continue for several seasons (stopping condition). To be specific, LCA is adopted [183] [184] in cloud computing for solving scheduling optimization problem, based on the iterative process for solving the global optimization problem [185]. However, LCA algorithm has not been accepted for t-way testing strategies in solving combinatorial optimization problem.…”

Section: Human-based Techniquementioning

confidence: 99%

Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-Way Testing

2022

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Metaheuristic algorithm is a very important area of research that continuously improve in solving optimization problems. Nature-inspired is one of the classifications of metaheuristic algorithm that are becoming more popular among researchers for the last decades. Nature-inspired metaheuristic algorithms contributes significantly to tackling many standing complex problems (such as combinatorial tway testing problem) and achieving optimal results. One challenge in this area is combinatorial explosion problem which always intended to find the most optimal final test suite that will cover all combinations of a given interaction strength. As such, test case generation is selected as the most active research area in combinatorial t-way testing as Non-deterministic Polynomial-time hardness (NP-hard). However, not all metaheuristics are effectively adopted in combinatorial t-way testing, some proved to be effective and thus have been popular tools selected for optimization whilst others are not adopted. 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. The purpose of this review is to revisit and carry out up-to-date review on these distinguished algorithms with their respective current state of use. This is to inspire future research in the field of combinatorial t-way testing for better optimization. Thus, we found that all metaheuristics has a simple structure to be adopted in different areas for becoming a more efficient in optimization. Finally, we suggested some future paths of investigation for researchers who are interested in the combinatorial t-way testing field to employ more of these algorithms by tuning their parameters setting to achieve an optimal solution.

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Section: Human-based Techniquementioning

confidence: 99%