Optimization of Distribution Routes by Hybrid DNA-ACO Algorithm

Huang, Jundong; Teng, Fei

doi:10.1109/aiam48774.2019.00084

Cited by 4 publications

(4 citation statements)

References 5 publications

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Section: Discussionmentioning

confidence: 99%

“…Similarly, logistic risk consisting of the absence of cold chain availability, counterfeit drugs, lack of personnel and traffic congestion, can be alleviated by network optimization (Huang and Fei, 2019), a robust and sophisticated cold chain with increased capacity (Mohsin and Yellampalli, 2018;Srivastava et al, 2021) and real-time location visibility (Mohsin and Yellampalli, 2018). This risk can also be mitigated with better tracking, traceability and transparency (Musamih et al, 2021), which can be achieved using the latest technologies like blockchain, IoT, machine learning, etc (Ahmadi et al, 2020;Singh et al, 2020;Trenfield et al, 2019).…”

Section: Mitigation Strategiesmentioning

confidence: 99%

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Supply chain risk factor assessment of Indian pharmaceutical industry for performance improvement

Sharma

Kumar

Arora

2022

IJPPM

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PurposeThe purpose of the present work is to improve the industry performance by identifying and quantifying the risks faced by the Indian pharmaceutical industry (IPI). The risk values for the prominent risks and overall industry are determined based on the four risk parameters, which would help determine the most contributive risks for mitigation.Design/methodology/approachAn extensive literature survey was done to identify the risks, which were also validated by industry experts. The finalized risks were then evaluated using the fuzzy synthetic evaluation (FSE) method, which is the most suitable approach for the risk assessment with parameters having a set of different risk levels.FindingsThe three most contributive sub-risks are counterfeit drugs, demand fluctuations and loss of customers due to partners' poor service performance, while the main risks obtained are demand, financial and logistics. Also, the overall risk value indicates that the industry faces medium to high risk.Practical implicationsThe study identifies the critical risks which need to be mitigated for an efficient industry. The industry is most vulnerable to the demand risk category. Therefore, the managers should minimize this risk by mitigating its sub-risks, like demand fluctuations, bullwhip effect, etc. Another critical sub-risk, the counterfeit risk, should be managed by adopting advanced technologies like blockchain, artificial intelligence, etc.Originality/valueThere is insufficient literature focusing on risk quantification. Therefore, this work addresses this gap and obtains the industry's most critical risks. It also discusses suitable mitigation strategies for better industry performance.

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Section: Discussionmentioning

confidence: 99%

Section: Mitigation Strategiesmentioning

confidence: 99%

Supply chain risk factor assessment of Indian pharmaceutical industry for performance improvement

Sharma

Kumar

Arora

2022

IJPPM

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“…A distribution route optimization model using DNA computing and the Ant Colony Optimization (ACO) algorithm is proposed by Huang and Fei [17] based on an analysis of the special characteristics for the transport of biological such as room temperature and delivery in a certain range of time. The proposed DNA-ACO algorithm managed to minimize costs more efficiently than algorithms such as ACO and fish swarm ant colony optimization (FSACO).…”

Section: Related Workmentioning

confidence: 99%

COVID-19 Vaccines distribution routes with bioinspired metaheuristic algorithms: Resoluteness

Estrada Moreno,

Valdovinos Rosas,

Loza Hernandez

et al. 2024

IEEE Latin Am. Trans.

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The global emergency of COVID-19 caused by the SARS-CoV-2 virus at the end of 2019, it was without a doubt a critical and historical point for society in general; for instance, the effective development of vaccines, as well as the efficient distribution of them; They were an unprecedented challenge to slow down the spread or mitigate its impact on societies around the world. This article specifies three bio-inspired metaheuristic algorithms (genetic algorithm, particle swarm optimization algorithm, and artificial bee colony algorithm) that were used in the context of the capacitated vehicle routing problem to generate vaccine distribution routes, specifically, COVID-19 vaccine for over 18 years old the first and the second doses applications in Mexico, particularly in the State of Mexico. The quality of the solutions obtained by these algorithms is compared, and the performance of the particle swarm optimization (PSO) algorithm being superior in solution quality. The results show that the construction of vaccine distribution routes applying bio-inspired algorithms determines reliable scenarios that support the decisionmaking of the personnel dedicated to carrying out this activity.

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“…Ref. [ 53 ] proposed a novel DNA-ant colony algorithm with Levy flight characteristics. The algorithm uses the disturbance of Levy flight characteristics to prevent the basic algorithm from falling into the local optimum and uses DNA crossover and mutation operations to control the algorithm parameters, thereby shortening the search time and improving the search accuracy.…”

Section: Swarm Intelligence and Its Application In Image Processingmentioning

confidence: 99%

Application of Swarm Intelligence Optimization Algorithms in Image Processing: A Comprehensive Review of Analysis, Synthesis, and Optimization

Cao

et al. 2023

Biomimetics

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Image processing technology has always been a hot and difficult topic in the field of artificial intelligence. With the rise and development of machine learning and deep learning methods, swarm intelligence algorithms have become a hot research direction, and combining image processing technology with swarm intelligence algorithms has become a new and effective improvement method. Swarm intelligence algorithm refers to an intelligent computing method formed by simulating the evolutionary laws, behavior characteristics, and thinking patterns of insects, birds, natural phenomena, and other biological populations. It has efficient and parallel global optimization capabilities and strong optimization performance. In this paper, the ant colony algorithm, particle swarm optimization algorithm, sparrow search algorithm, bat algorithm, thimble colony algorithm, and other swarm intelligent optimization algorithms are deeply studied. The model, features, improvement strategies, and application fields of the algorithm in image processing, such as image segmentation, image matching, image classification, image feature extraction, and image edge detection, are comprehensively reviewed. The theoretical research, improvement strategies, and application research of image processing are comprehensively analyzed and compared. Combined with the current literature, the improvement methods of the above algorithms and the comprehensive improvement and application of image processing technology are analyzed and summarized. The representative algorithms of the swarm intelligence algorithm combined with image segmentation technology are extracted for list analysis and summary. Then, the unified framework, common characteristics, different differences of the swarm intelligence algorithm are summarized, existing problems are raised, and finally, the future trend is projected.

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Optimization of Distribution Routes by Hybrid DNA-ACO Algorithm

Cited by 4 publications

References 5 publications

Supply chain risk factor assessment of Indian pharmaceutical industry for performance improvement

Supply chain risk factor assessment of Indian pharmaceutical industry for performance improvement

COVID-19 Vaccines distribution routes with bioinspired metaheuristic algorithms: Resoluteness

Application of Swarm Intelligence Optimization Algorithms in Image Processing: A Comprehensive Review of Analysis, Synthesis, and Optimization

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