Scopus
YÖKSİS DOI Eşleşti
SJR Q1
A new MILP model proposal in feed formulation and using a hybrid-linear binary PSO (H-LBP) approach for alternative solutions
Neural Computing and Applications · Ocak 2018
YÖKSİS Kayıtları
A new MILP model proposal in feed formulation and using a hybrid linear binary PSO H LBP approach for alternative solutions
NEURAL COMPUTING & APPLICATIONS · 2018 SCI-Expanded
Doç. Dr. MEHMET AKİF ŞAHMAN →
A new MILP model proposal in feed formulation and using a hybrid linear binary PSO H LBP approach for alternative solutions
Neural Computing and Applications · 2016 SCI-Expanded
Doç. Dr. MEHMET AKİF ŞAHMAN →
A new MILP model proposal in feed formulation and using a hybrid linear binary PSO H LBP approach for alternative solutions
Neural Computing and Applications · 2016 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
A new MILP model proposal in feed formulation and using a hybrid-linear binary PSO (H-LBP) approach for alternative solutions
Neural Computing and Applications · 2018 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
YÖKSİS Kayıtları — ISSN Eşleşmesi
Automatic detection and classification of rotor cage faults in squirrel cage induction motor
2010 ISSN: 0941-0643 SCI-Expanded 6 atıf
Prof. Dr. HAYRİ ARABACI →
Short term load forecasting using fuzzy logic and ANFIS
2015 ISSN: 0941-0643 SCI-Expanded 1 atıf
Dr. Öğr. Üyesi HASAN HÜSEYİN ÇEVİK →
Determination of induction motor parameters with differential evolution algorithm
2012 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
Short term load forecasting using fuzzy logic and ANFIS
2015 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
Fuzzy logic based induction motor protection system
2013 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
Determination of induction motor parameters with differential evolution algorithm
2012 ISSN: 0941-0643 SCI-Expanded
Doç. Dr. TAHİR SAĞ →
Cost optimization of mixed feeds with the particle swarm optimization method
2013 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
A combination of Genetic Algorithm Particle Swarm Optimization and Neural Network for palmprint recognition
2013 ISSN: 0941-0643 SCI-Expanded 1 atıf
Prof. Dr. ADEM ALPASLAN ALTUN →
Cost optimization of mixed feeds with the particle swarm optimization method
2013 ISSN: 0941-0643 SCI-Expanded
Doç. Dr. MEHMET AKİF ŞAHMAN →
Fuzzy logic based induction motor protection system
2013 ISSN: 0941-0643 SCI
Dr. Öğr. Üyesi OKAN UYAR →
A new MILP model proposal in feed formulation and using a hybrid linear binary PSO H LBP approach for alternative solutions
2018 ISSN: 0941-0643 SCI-Expanded Q1
Doç. Dr. MEHMET AKİF ŞAHMAN →
FPGA based self organizing fuzzy controller for electromagnetic filter
2016 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. İSMAİL SARITAŞ →
FPGA-based self-organizing fuzzy controller for electromagnetic filter
2017 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. İSMAİL SARITAŞ →
A new MILP model proposal in feed formulation and using a hybrid linear binary PSO H LBP approach for alternative solutions
2016 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
Application of fuzzy C-means clustering algorithm to spectral features for emotion classification from speech
2018 ISSN: 0941-0643 SCI-Expanded Q1
Prof. Dr. HUMAR KAHRAMANLI ÖRNEK →
A new denoising method for fMRI based on weighted three-dimentional wavelet transform
2018 ISSN: 0941-0643 SCI-Expanded
Dr. Öğr. Üyesi GÜZİN ÖZMEN →
FPGA-based self-organizing fuzzy controller for electromagnetic filter
2017 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. İSMAİL SARITAŞ →
A new MILP model proposal in feed formulation and using a hybrid-linear binary PSO (H-LBP) approach for alternative solutions
2018 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
Hybrid breast cancer detection tem via neural network and feature ion based on SBS SFS and PCA
2013 ISSN: 0941-0643 SCI-Expanded 5 atıf
Dr. Öğr. Üyesi ONUR İNAN →
FPGA-based self-organizing fuzzy controller for electromagnetic filter
2017 ISSN: 0941-0643 SCI-Expanded
Doç. Dr. İLKER ALİ ÖZKAN →
Makale Bilgileri
ISSN09410643
Yayın TarihiOcak 2018
Cilt / Sayfa29 · 537-552
Scopus ID2-s2.0-84978747592
Özet
Large-scale feed factories may have multiple production and storage facilities. Any production facility uses its own available raw materials while performing feed formulation. However, ensuring a reasonable cost is achieved, and the desired quality criteria are met, may require obtaining a certain amount of raw material from other facilities. Selecting a specific amount of raw materials among many raw materials in different facilities requires many combinations to be tried out. Providing solutions, especially when there is a large amount of the raw material, may be costly and take more time. A new mixed-integer linear programming (MILP) model that specifies the type of material and the amount of the material to be selected from external facilities has been proposed in this study. When deterministic methods like MILP are used, only one solution result is obtained. However, when the decision-maker would like to see alternative results, solution constraints can be mitigated and a solution provided within the same or similar time. A new method named hybrid-linear binary PSO (H-LBP) has been proposed in this study for the problems that the decision-maker had limited time for and for which the solution results were required in a shorter time. Continuous particle swarm optimization, which works as a hybrid with linear programming, has been used in this method. The new model proposed in this study was tested on the mixed feeds for sheep, cattle and rabbit species by using both MILP and the proposed H-LBP methods. Raw materials determined by the model were added to the mixture, and the cost in each of the three species was observed to go down. In addition, different alternative solutions at reasonable cost and similar quality were presented to the producer/decision-maker in a shorter time.
Yazarlar (3)
1
Mehmet Akif Şahman
2
A. A. Altun
3
Abdullah Oktay Dündar
Anahtar Kelimeler
Binary particle swarm optimization
Feed mix optimization
Linear programming
Mixed-integer linear programming
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Neural Computing and Applications
Q1
SJR Skoru1,102
H-Index146
YayıncıSpringer London
ÜlkeUnited Kingdom
Artificial Intelligence (Q1)
Software (Q1)
Metrikler
10
Atıf
3
Yazar
4
Anahtar Kelime