In recent years, the double-layered multi-head weighers whose hoppers are arranged in two levels are widely used in the accurate and reliable weighing for packing food products. The weighing processes are mathematically modeled into a single objective optimization problems. The objective of packing problem is to minimize the total weight of combined hoppers for a package under the condition that the total weight must be no less than a specified target weight. This paper proposes a novel single objective optimization approach for double-layered multi-head weighing process. More precisely, relying on a new bound on the optimal weight, this study accurately determines the number of hoppers to be combined at each packing operation, and find the best possible hopper combination using the single-objective algorithm. This method significantly speeds up the packing process as a whole. According to the present approach, the candidate number of hoppers to be combined can be taken one or two integral values. The probability that the accurate number of hoppers to be combined becomes one integral value is explicitly calculated, which is the performance factor to the previous one. In addition, results from the numerical experiments to show the effectiveness of the proposed approach are presented.
Published in | Mathematical Modelling and Applications (Volume 9, Issue 3) |
DOI | 10.11648/j.mma.20240903.12 |
Page(s) | 61-69 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Double Layer, Multi-Head Weigher, Packaging Process, Optimization, Single Objective Problem
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APA Style
An, P., Hong, C., Ri, R., Yu, C., O, C. (2024). An Improved Single Objective Optimization Approach for Double-Layered Multi-Head Weighing Process. Mathematical Modelling and Applications, 9(3), 61-69. https://doi.org/10.11648/j.mma.20240903.12
ACS Style
An, P.; Hong, C.; Ri, R.; Yu, C.; O, C. An Improved Single Objective Optimization Approach for Double-Layered Multi-Head Weighing Process. Math. Model. Appl. 2024, 9(3), 61-69. doi: 10.11648/j.mma.20240903.12
AMA Style
An P, Hong C, Ri R, Yu C, O C. An Improved Single Objective Optimization Approach for Double-Layered Multi-Head Weighing Process. Math Model Appl. 2024;9(3):61-69. doi: 10.11648/j.mma.20240903.12
@article{10.11648/j.mma.20240903.12, author = {Pom An and Chol-Jun Hong and Ryong-Yon Ri and Chol-Jun Yu and Chol-Jun O}, title = {An Improved Single Objective Optimization Approach for Double-Layered Multi-Head Weighing Process }, journal = {Mathematical Modelling and Applications}, volume = {9}, number = {3}, pages = {61-69}, doi = {10.11648/j.mma.20240903.12}, url = {https://doi.org/10.11648/j.mma.20240903.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mma.20240903.12}, abstract = {In recent years, the double-layered multi-head weighers whose hoppers are arranged in two levels are widely used in the accurate and reliable weighing for packing food products. The weighing processes are mathematically modeled into a single objective optimization problems. The objective of packing problem is to minimize the total weight of combined hoppers for a package under the condition that the total weight must be no less than a specified target weight. This paper proposes a novel single objective optimization approach for double-layered multi-head weighing process. More precisely, relying on a new bound on the optimal weight, this study accurately determines the number of hoppers to be combined at each packing operation, and find the best possible hopper combination using the single-objective algorithm. This method significantly speeds up the packing process as a whole. According to the present approach, the candidate number of hoppers to be combined can be taken one or two integral values. The probability that the accurate number of hoppers to be combined becomes one integral value is explicitly calculated, which is the performance factor to the previous one. In addition, results from the numerical experiments to show the effectiveness of the proposed approach are presented. }, year = {2024} }
TY - JOUR T1 - An Improved Single Objective Optimization Approach for Double-Layered Multi-Head Weighing Process AU - Pom An AU - Chol-Jun Hong AU - Ryong-Yon Ri AU - Chol-Jun Yu AU - Chol-Jun O Y1 - 2024/09/06 PY - 2024 N1 - https://doi.org/10.11648/j.mma.20240903.12 DO - 10.11648/j.mma.20240903.12 T2 - Mathematical Modelling and Applications JF - Mathematical Modelling and Applications JO - Mathematical Modelling and Applications SP - 61 EP - 69 PB - Science Publishing Group SN - 2575-1794 UR - https://doi.org/10.11648/j.mma.20240903.12 AB - In recent years, the double-layered multi-head weighers whose hoppers are arranged in two levels are widely used in the accurate and reliable weighing for packing food products. The weighing processes are mathematically modeled into a single objective optimization problems. The objective of packing problem is to minimize the total weight of combined hoppers for a package under the condition that the total weight must be no less than a specified target weight. This paper proposes a novel single objective optimization approach for double-layered multi-head weighing process. More precisely, relying on a new bound on the optimal weight, this study accurately determines the number of hoppers to be combined at each packing operation, and find the best possible hopper combination using the single-objective algorithm. This method significantly speeds up the packing process as a whole. According to the present approach, the candidate number of hoppers to be combined can be taken one or two integral values. The probability that the accurate number of hoppers to be combined becomes one integral value is explicitly calculated, which is the performance factor to the previous one. In addition, results from the numerical experiments to show the effectiveness of the proposed approach are presented. VL - 9 IS - 3 ER -