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:: Volume 5, Issue 1 (9-2016) ::
منادی 2016, 5(1): 45-52 Back to browse issues page
Performance assessment Bio- Inspired algorithms for solving backpack in the form of objective function minimization.
Mahtab Roozbahani * , Meysam Moradi , Parvaneh Mansoori
Abstract:   (3589 Views)

In mathematics and computer science an optimization problem, the problem is finding the best solution among all possible solutions. Given the importance of the knapsack in computer sciences, different algorithms are used to solve it. Knapsack problem is a combinational problem of selectivity and the purpose of solving the most benefit by taking the capacity is the tolerable knapsack. Since the knapsack is a problem of constrained maximization. In this study, a mathematical model in the form of a function unlimited minimization and designed for it, hen this model on Particle Swarm Optimization , Firefly Algorithm and Artificial Bee Colony has been implemented in MATLAB software environment, The results show that the artificial bee colony algorithm, the model is better than the other two algorithms .The advantage of this model is the objective function , because minimization and unlimited models , to implement with many  Bio-Inspired algorithms.

Keywords: Knapsack Problem, Particle Swarm Optimization Algorithm, Firefly Algorithm, Artificial Bee Colony Algorithm.
Full-Text [PDF 2963 kb]   (895 Downloads)    
Type of Study: Research Article | Subject: Special
Received: 2016/02/27 | Accepted: 2017/04/7 | Published: 2017/04/7
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roozbahani M, moradi M, mansoori P. Performance assessment Bio- Inspired algorithms for solving backpack in the form of objective function minimization.. منادی 2016; 5 (1) :45-52
URL: http://monadi.isc.org.ir/article-1-54-en.html


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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 5, Issue 1 (9-2016) Back to browse issues page
دوفصل نامه علمی  منادی امنیت فضای تولید و تبادل اطلاعات( افتا) Biannual Journal Monadi for Cyberspace Security (AFTA)
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