Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Naglaa Ragaa"'
Publikováno v:
International Journal of Industrial Engineering and Production Research, Vol 35, Iss 1, Pp 74-87 (2024)
Harris Hawks Optimization (HHO) algorithm, which is a new metaheuristic algorithm that has shown promising results in comparison to other optimization methods. The surprise pounce is a cooperative behavior and chasing style exhibited by Harris' Hawks
Externí odkaz:
https://doaj.org/article/07cc6d8749cf4f35aaab177c12efa751
Publikováno v:
Journal of Mechanics of Continua and Mathematical Sciences, Vol 19, Iss 1, Pp 27-46 (2024)
The usage of nature-inspired meta-heuristic algorithms is increasing due to their simplicity and versatility. These algorithms are widely used in numerous domains, especially in scientific fields such as operations research, computer science, artific
Externí odkaz:
https://doaj.org/article/e7b2f8ee90094f1da2ee3c149061d5a0
Publikováno v:
Baghdad Science Journal, Vol 21, Iss 5 (2024)
The Multi-objective de novo programming method is an effective tool to deal with the optimal system design by determining the optimal level of resources allocation (RA) to improve the value of the objective functions according to the price of resourc
Externí odkaz:
https://doaj.org/article/95f064720d744aa9b3c88b08d6431d78
Publikováno v:
MethodsX, Vol 11, Iss , Pp 102276- (2023)
The differential evolution algorithm is one of the promising natural inspired population-based metaheuristic algorithms that attracted the attention of researchers in the recent years. This paper presents a new mutation strategy called DE/current-to-
Externí odkaz:
https://doaj.org/article/bc010b767e2745848c18dfbb1546a6f9
Publikováno v:
International Journal of Industrial Engineering and Production Research, Vol 34, Iss 1, Pp 1-9 (2023)
Researchers in many fields, such as operations research, computer science, AI engineering, and mathematical engineering, extra, are increasingly adopting nature-inspired metaheuristic algorithms because of their simplicity and flexibility. Natural me
Externí odkaz:
https://doaj.org/article/c6112522fbff484b8111581992cb2ec1
Publikováno v:
International Journal of Production Management and Engineering, Vol 10, Iss 1, Pp 13-22 (2022)
The U-shaped assembly lines help to have more flexibility than the straight assembly lines, where the operators can perform tasks in both sides of the line, the entrance and the exit sides. Having more than one operator in any station of the line can
Externí odkaz:
https://doaj.org/article/c262b5217bce4cd387dbe4abae12849c
Publikováno v:
Baghdad Science Journal; 2024, Vol. 21 Issue 5, p1649-1666, 18p
Publikováno v:
International Journal of ADVANCED AND APPLIED SCIENCES. 10:44-52
An iterative technique based on the use of parametric functions is proposed in this paper to obtain the best preferred optimal solution of a multi-objective linear fractional programming problem (MOLFPP). Each fractional objective is transformed into
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb672491f7e97b15f3bc77bdd9cfeaf1
https://doi.org/10.21833/ijaas.2023.04.006
https://doi.org/10.21833/ijaas.2023.04.006
Publikováno v:
Production Engineering Archives. 29:14-22
Measuring the organization’s performance is essential for continuous improvement and operational excellence. Appropriate organizational measures include multiple dimensions. The relative importance of the multiple dimensions varies depending on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb7fd433a02c685a31e4d91b4a8eef30
https://doi.org/10.30657/pea.2023.29.3
https://doi.org/10.30657/pea.2023.29.3
Publikováno v:
International Journal of Applied Metaheuristic Computing. 13:1-18
This paper discusses the U-shaped assembly line balancing problem in case of stochastic processing time. The problem is formulated using chance-constrained programming and the greedy randomized adaptive search procedure is used to solve the problem.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7efecaaf8382bf3308ff520f2181b324
https://doi.org/10.4018/ijamc.298310
https://doi.org/10.4018/ijamc.298310