Application of FWA-Artificial Fish Swarm Algorithm in the Location of Low-Carbon Cold Chain Logistics Distribution Center in Beijing-Tianjin-Hebei Metropolitan Area

Zhang, Liyi; Fu, Mingyue; Teng, Fei; Xuhua, Pan

doi:10.1155/2021/9945583

Cited by 3 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The same way, Zhang et al [19], suggest an FSA upgraded, including some FWA elements, and applying it to its optimization model of location-routing problem-based lowcarbon cold chain that includes fixed costs, transportation cost, cost of load damage, cooling cost, emissions of carbon cost, and penalization cost.…”

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.

View full text Add to dashboard Cite

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.

show abstract

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.

View full text Add to dashboard Cite

show abstract

Kahramanmaraş İlindeki Dondurma Üreticilerinin Soğuk Zincir Taşıyıcı Seçiminde Kullanmış Oldukları Kriterler Ve Bu Kriterlerin Önem Derecelerinin AHP Yöntemi İle Belirlenmesi

ŞEKER

KORKMAZ

2021

Finans Ekonomi Ve Sosyal Araştırmalar Dergisi

View full text Add to dashboard Cite

Bu çalışmada soğuk zincir taşıyıcı seçiminde kullanılabilecek bilimsel yöntemlerden birinin AHP tekniği olabileceği konusunda bir farkındalık yaratılmaya çalışılmıştır. AHP yöntemi uygulanmadan önce, ilk olarak yurt içi dondurma dağıtımı yapan taşıyıcı işletmelerin seçiminde kullanılacak kriterler literatürden yararlanarak belirlenmiştir. Daha sonra literatürden yararlanılarak belirlenen bu kriterlerin ağırlıklandırılması yapılmıştır. Bunun için Kahramanmaraş dondurma sektörüne hâkim büyük firmaların 10 yöneticisiyle uzman görüşü anketi gerçekleştirilmiştir. Anket çalışmasında öncelikle, literatür taraması sonucunda belirlenen kriterlerlerin her biri bir diğeriyle tek tek uzmanlar tarafından ikili karşılaştırmaya tabi tutulmuştur. Ardından AHP yönteminin tüm adımları uygulanmıştır. AHP yönteminin adımlarının uygulanması sonucunda; zamanında teslimat en önemli kriter, güvenilirlik ikinci, tecrübe üçüncü, ağ yönetimi dördüncü, soğuk zincir süreçlerinin inovasyonu ve etkinliği beşinci, bilgi teknolojileri altıncı, maliyet yedinci ve son olarak da esneklik sekizinci kriter olarak belirlenmiştir.

show abstract

Modified artificial fish swarm algorithm to solve unrelated parallel machine scheduling problem under fuzzy environment

Ibadi,

Rahman

2024

MATH

View full text Add to dashboard Cite

<p>Unrelated parallel machine scheduling problem (UPMSP) in a fuzzy environment is an active research area due to the fuzzy nature of most real-world problems. UPMSP is an NP-hard problem; thus, finding optimal solutions is challenging, particularly when multiple objectives need to be considered. Hence, a metaheuristic algorithm based on a modified artificial fish swarm algorithm (AFSA) is presented in this study to minimize the multi-objective makespan and total tardiness. Three modifications were made to the proposed algorithm. First, aspiration behavior was added to AFSA behaviors to increase effectiveness. Second, improved parameters such as step and visual were used to balance global search capability and convergence rate. Finally, a transformation method was injected to make the algorithm suitable for discrete optimization problems such as UPMSP. The proposed algorithm was compared with AFSA and five modified versions of AFSA to verify and measure the algorithm's effectiveness by conducting three different sizes of problems. Afterward, the Wilcoxon signed-rank test was used to statistically evaluate the algorithm's performance. The results indicate that the proposed algorithm significantly outperformed the other algorithms, especially for medium and large-sized problems.</p>

show abstract

Application of FWA-Artificial Fish Swarm Algorithm in the Location of Low-Carbon Cold Chain Logistics Distribution Center in Beijing-Tianjin-Hebei Metropolitan Area

Cited by 3 publications

References 7 publications

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

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

Kahramanmaraş İlindeki Dondurma Üreticilerinin Soğuk Zincir Taşıyıcı Seçiminde Kullanmış Oldukları Kriterler Ve Bu Kriterlerin Önem Derecelerinin AHP Yöntemi İle Belirlenmesi

Modified artificial fish swarm algorithm to solve unrelated parallel machine scheduling problem under fuzzy environment

Contact Info

Product

Resources

About