Research on group animation design technology based on artificial fish swarm algorithm

Yuan, Tian; Li, You; Lin, Pao‐Hwa; Morris, Harry

doi:10.3233/jifs-179475

Cited by 8 publications

(6 citation statements)

References 18 publications

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“…The FSA is a new intelligent swarm approach by the natural feeding behavior of fish that this algorithm first developed by Li (2002) that includes following, searching, and swarming behaviors. FSA is a new method that has been successfully employed in network design, supply chain systems, and location, allocation, inventory problems ( Tian et al, 2020 ). In this algorithm, the satisfaction of food for the fish is demonstrated as

, and a fish is indicated by its

-dimensional position

.…”

Section: Presented Hybrid Meta-heuristic Algorithmsmentioning

confidence: 99%

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An integrated sustainable medical supply chain network during COVID-19

Goodarzian

Taleizadeh

Ghasemi

et al. 2021

Engineering Applications of Artificial Intelligence

189

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Nowadays, in the pharmaceutical industry, a growing concern with sustainability has become a strict consideration during the COVID-19 pandemic. There is a lack of good mathematical models in the field. In this research, a production–distribution–inventory–allocation–location problem in the sustainable medical supply chain network is designed to fill this gap. Also, the distribution of medicines related to COVID-19 patients and the periods of production and delivery of medicine according to the perishability of some medicines are considered. In the model, a multi-objective, multi-level, multi-product, and multi-period problem for a sustainable medical supply chain network is designed. Three hybrid meta-heuristic algorithms, namely, ant colony optimization, fish swarm algorithm, and firefly algorithm are suggested, hybridized with variable neighborhood search to solve the sustainable medical supply chain network model. Response surface method is used to tune the parameters since meta-heuristic algorithms are sensitive to input parameters. Six assessment metrics were used to assess the quality of the obtained Pareto frontier by the meta-heuristic algorithms on the considered problems. A real case study is used and empirical results indicate the superiority of the hybrid fish swarm algorithm with variable neighborhood search.

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, and a fish is indicated by its

-dimensional position

.…”

Section: Presented Hybrid Meta-heuristic Algorithmsmentioning

confidence: 99%

“…Eventually, in the main loop, the VNS is represented on the obtained best solution. Then, for more details about the FSA algorithm, researchers can refer to Tian et al (2020) . The pseudo-code of the general scheme of the HFSA-VNS algorithm is indicated in Fig.…”

Section: Presented Hybrid Meta-heuristic Algorithmsmentioning

confidence: 99%

An integrated sustainable medical supply chain network during COVID-19

Goodarzian

Taleizadeh

Ghasemi

et al. 2021

Engineering Applications of Artificial Intelligence

189

View full text Add to dashboard Cite

show abstract

“…Maya's tools will be utilized to create the 3D environments, animations, and character designs. Group animation effects are achieved by combining many routes [21]. In article [22], APTOensures the production of huge rangegrouping animation in real time, the grouping animation characterization architecture and the space separation perception algorithm are both examined and developed.…”

Section: Related Workmentioning

confidence: 99%

“…88 Informatica 48 (2024) 83-96 D. Chen used in texture analysis to increase the realism of surface patterns and styles. [21] The route for group behavior based on avoiding collisions and detection is designed using the enhanced artificial fish swarm method, and the obtained path data is subsequently imported into Maya.…”

Section: Refere Ncementioning

confidence: 99%

Animation Vr Scene Stitching Modeling Based on Genetic Algorithm

Chen

2024

IJCAI

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The process of seamlessly combining many Virtual reality (VR) scenes to create a continuous and engaging VR experience is known as VR scene stitching. It comprises stitching together several scenes or locations to provide smooth transitions between them without any noticeable seams or interruptions. Each VR scene is carefully designed and created, focusing on certain areas, objects, or events within the virtual environment. To enhance the expertise based on the already employed animation VRSSM (VR scene stitching modeling), more research is conducted on the animation VRSSM in conjunction with Genetic Algorithms (GA). The approach uses a wavelet transform (WT) to recover the scene's low-and high-frequency components for use in animation. Splicing criteria for the high-frequency coefficients are determined by comparing and filtering the convolution outcomes from 2 GA pattern operators. The GA sharpness assessment function and the 8 neighborhood local variance are used to determine the splice procedure for the low frequency coefficients; to produce the mosaic modeling of the stitching scene; the inverse WT is utilized. The subjective and objective assessment approaches are used together to examine the experimental outcomes. The data demonstrate that the GA achieves a higher quality splice (0.38) than the traditional splicing modeling. Rich edge information and great scene clarity are benefits of animation scene splicing modeling. The method suggested in this study outperforms the standard algorithm in terms of both qualitative and quantitative evaluation, and its implementation yields a potent synergistic impact on VR scene stitching.Povzetek: Raziskava izboljšuje združevanje VR scen z uporabo genetskih algoritmov in valčne transformacije, kar omogoča kakovostnejše in bolj jasne prehode med scenami.

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“…Although the traditional AFSA to find the optimal solution has the benefit of simple operation and fast convergence, there are also numerous disadvantages: the algorithm converges slowly at a later stage; the optimal solution is a range is not precise; parameter settings can affect the performance [19,20]. To address these problems,On the basis of the traditional artificial fish swarm algorithm, an improved logistics distribution method of artificial fish swarm algorithm is proposed by adopting improved strategies such as fish swarm visual field adaptation, moving step length adaptation and parameter setting, which can accelerate the algorithm convergence speed and improve the accuracy and efficiency of the algorithm.the study first uses the control variable method to find the optimal value of the algorithm parameters, so as to improve the accuracy and efficiency to find the optimal solution.…”

Section: Vehicle Path Optimization Strategy Based On Afsa Algorithmmentioning

confidence: 99%

A Dynamic Path Optimization Model of IOT Delivery Vehicles for E-commerce Logistics Distribution

2023

SCPE

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Logistics and distribution is a vital link to guarantee the stable supply of the e-commerce market and the healthy development of the industry. With the constant growth of the e-commerce, the efficiency and service quality of logistics and distribution have been paid more and more attention to. Therefore, the study firstly Considering distribution fixed cost, transportation penalty cost and carbon emission cost, the vehicle routing optimization model is transformed into the lowest transportation cost model, then uses an improved traditional artificial fish swarm algorithm to find the optimum way for this model, and finally verifies its performance and applicability through experiments. The performance test results show that the algorithm finds the optimal solution 3589 and 3590 in 63 and 78 iterations in the Oxford Robot Car dataset and Apollo Scape dataset, respectively; the average running time of the algorithm is 11.864s and 11.967s in the 10 operation time tests; in the operation function test, the algorithm. The algorithm was able to overcome the local optimal solution problem. The applicability simulation shows that this algorithm stabilizes after 53 iterations, the minimum cost of the optimal solution of the model is $41,224, and the total distance of distribution is 9035 km. The research algorithm is fast in finding the optimal value, which is close to it, indicating that the algorithm is highly efficient and reliable, and can greatly optimize the path of e-commerce logistics delivery vehicles, and give a theoretical foundation for the optimization of logistics delivery paths in other industries.

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Research on group animation design technology based on artificial fish swarm algorithm

Cited by 8 publications

References 18 publications

An integrated sustainable medical supply chain network during COVID-19

An integrated sustainable medical supply chain network during COVID-19

Animation Vr Scene Stitching Modeling Based on Genetic Algorithm

A Dynamic Path Optimization Model of IOT Delivery Vehicles for E-commerce Logistics Distribution

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