A Global Best-guided Firefly Algorithm for Engineering Problems

Zare, Mohsen; Ghasemi, Maryam; Zahedi, Amir; Golalipour, Keyvan; Mohammadi, Soleiman Kadkhoda; Mirjalili, Seyedali; Abualigah, Laith

doi:10.1007/s42235-023-00386-2

Cited by 54 publications

(7 citation statements)

References 125 publications

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“…To address this issue, reverse learning is introduced into the bee colony algorithm. This approach introduces disturbances to the algorithm, particularly in the early iterations, to enhance the population’s diversity [ 27 ]. Gaussian functions are utilized in the optimization process to adjust the magnitude of disturbances.…”

Section: Applications Of Chatgpt and Iot Technology In Medical Inform...mentioning

confidence: 99%

Designing a medical information diagnosis platform with IoT integration

Liu,

Guan,

Bai

et al. 2024

Heliyon

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Section: Applications Of Chatgpt and Iot Technology In Medical Inform...mentioning

confidence: 99%

Designing a medical information diagnosis platform with IoT integration

Liu,

Guan,

Bai

et al. 2024

Heliyon

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“…The DO algorithm uses Brownian motion obeying normal distribution to simulate the movement track of dandelion seeds, so that individuals can easily traverse more search areas in the iterative process. Average position information after the rising stage reflects the stability of dande-lion descent, which is helpful for the whole population to search and develop the optimal individual areas, as shown in Formula (10).…”

Section: Dandelion Optimization Algorithmmentioning

confidence: 99%

“…Traditional optimization algorithms can no longer meet requirements, and more efficient intelligent optimization algorithms are urgently needed. Therefore, people are focusing on swarm intelligence optimization algorithms, such as gray wolf optimization (GWO) [8], the Whale Optimization Algorithm (WOA) [9], Firefly FA (Firefly Algorithm) [10] and the Sparrow Search Algorithm (SSA) [11]. These algorithms are not limited in search space and objective function form and have good optimization ability, so they have been widely used in real life and engineering fields [12,13].…”

Section: Introductionmentioning

confidence: 99%

Solving Engineering Optimization Problems Based on Multi-Strategy Particle Swarm Optimization Hybrid Dandelion Optimization Algorithm

Tang,

Cao,

Chen

et al. 2024

Biomimetics

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In recent years, swarm intelligence optimization methods have been increasingly applied in many fields such as mechanical design, microgrid scheduling, drone technology, neural network training, and multi-objective optimization. In this paper, a multi-strategy particle swarm optimization hybrid dandelion optimization algorithm (PSODO) is proposed, which is based on the problems of slow optimization speed and being easily susceptible to falling into local extremum in the optimization ability of the dandelion optimization algorithm. This hybrid algorithm makes the whole algorithm more diverse by introducing the strong global search ability of particle swarm optimization and the unique individual update rules of the dandelion algorithm (i.e., rising, falling and landing). The ascending and descending stages of dandelion also help to introduce more changes and explorations into the search space, thus better balancing the global and local search. The experimental results show that compared with other algorithms, the proposed PSODO algorithm greatly improves the global optimal value search ability, convergence speed and optimization speed. The effectiveness and feasibility of the PSODO algorithm are verified by solving 22 benchmark functions and three engineering design problems with different complexities in CEC 2005 and comparing it with other optimization algorithms.

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“…In addition, there exist metaheuristic optimization algorithms like DETDO (Adaptive Hybrid Dandelion Optimizer) (Hu et al 2023) and the Global Best-guided Firefly Algorithm (Zare et al 2023) which are commonly used in solving engineering optimization problems. These metaheuristic algorithms are versatile, heuristic-driven techniques for solving complex, non-linear optimization problems.…”

Section: Techniques For Vendor Selectionmentioning

confidence: 99%

A framework for software vendor selection by applying Inconsistency and Conflict Removal (ICR) method

Rani,

Mishra,

Omerovic

2023

Int J Syst Assur Eng Manag

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In a software ecosystem, companies’ stakeholders make various decisions and perform various tasks to ensure the strategic and architectural goals of the company. Analyzing vendor capabilities and making decisions to select software vendors requires expert professionals. To analyze vendors’ capabilities and accessing them according to the company’s strategic and architectural goals is presently an ad-hoc and manual process. Presently, there is no systematic process for ‘vendor analysis and selection’ specifically for the software industry. Therefore, this study introduces a novel framework which elaborates all the tasks required for vendor proposal evaluation. It also includes the automatic detection of inconsistencies and conflicts prevalent during this process. A new method called ‘Inconsistency and Conflict Removal (ICR)’ is proposed as part of this framework. ICR automates the process of spotting inconsistencies and conflicts by taking scores of vendor capabilities as input reported by different decision-makers. Further, to illustrate this framework, ‘a case of Hospital’ has been considered. This study provides valuable knowledge that would facilitate organizations in software vendor selection. It will lead to substantial savings in terms of economics, such as actual costs, time, and improved administrative processes.

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A Global Best-guided Firefly Algorithm for Engineering Problems

Cited by 54 publications

References 125 publications

Designing a medical information diagnosis platform with IoT integration

Designing a medical information diagnosis platform with IoT integration

Solving Engineering Optimization Problems Based on Multi-Strategy Particle Swarm Optimization Hybrid Dandelion Optimization Algorithm

A framework for software vendor selection by applying Inconsistency and Conflict Removal (ICR) method

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