A new MILP model proposal in feed formulation and using a hybrid-linear binary PSO (H-LBP) approach for alternative solutions
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 a...
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| Vydáno v: | Neural computing & applications Ročník 29; číslo 2; s. 537 - 552 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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London
Springer London
01.01.2018
Springer Nature B.V |
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| ISSN: | 0941-0643, 1433-3058 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Dündar, Abdullah Oktay Altun, Adem Alparslan Şahman, Mehmet Akif |
| Author_xml | – sequence: 1 givenname: Mehmet Akif surname: Şahman fullname: Şahman, Mehmet Akif email: asahman@selcuk.edu.tr organization: Guneysinir Vocational School, University of Selcuk – sequence: 2 givenname: Adem Alparslan surname: Altun fullname: Altun, Adem Alparslan organization: Department of Computer Engineering, Faculty of Technology, University of Selcuk – sequence: 3 givenname: Abdullah Oktay surname: Dündar fullname: Dündar, Abdullah Oktay organization: Akoren Vocational School, University of Selcuk |
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| Keywords | Binary particle swarm optimization Linear programming Feed mix optimization Mixed-integer linear programming |
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| SubjectTerms | Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Decision making Image Processing and Computer Vision Industrial plants Integer programming Linear programming Original Article Particle swarm optimization Probability and Statistics in Computer Science Raw materials Sheep Storage facilities |
| Title | A new MILP model proposal in feed formulation and using a hybrid-linear binary PSO (H-LBP) approach for alternative solutions |
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