Higher desirability in solving multiple response optimization problems with committee machine
Many industrial problems need to be optimized several responses simultaneously. These problems are named multiple response optimization (MRO) and they can have different objectives such as Target, Minimization or Maximization. Committee machine (CM) as a set of some experts such as some artificial n...
| Những tác giả chính: | , , , , , , |
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| Định dạng: | Bài viết |
| Ngôn ngữ: | English |
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Trans Tech Publications
2014
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| Truy cập trực tuyến: | http://psasir.upm.edu.my/id/eprint/22878/1/Higher%20desirability%20in%20solving%20multiple%20response%20optimization%20problems%20with%20committee%20machine.pdf |
| _version_ | 1825925243278983168 |
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| author | Golestaneh, Seyed Jafar Ismail, Napsiah Mohd Ariffin, Mohd Khairol Anuar Tang, Sai Hong Naeini, Hassan Moslemi Maghsoudi, Ali Asghar Firoozi, Zahra |
| author_facet | Golestaneh, Seyed Jafar Ismail, Napsiah Mohd Ariffin, Mohd Khairol Anuar Tang, Sai Hong Naeini, Hassan Moslemi Maghsoudi, Ali Asghar Firoozi, Zahra |
| author_sort | Golestaneh, Seyed Jafar |
| collection | UPM |
| description | Many industrial problems need to be optimized several responses simultaneously. These problems are named multiple response optimization (MRO) and they can have different objectives such as Target, Minimization or Maximization. Committee machine (CM) as a set of some experts such as some artificial neural networks (ANNs) in combination with genetic algorithm (GA) is applied for modeling and optimization of MRO problems. In addition, optimization usually is done on Global Desirability (GD) function. Current article is a development for recent authors' work to determine economic run number for application of CM and GA in MRO problem solving. This study includes a committee machine with four different ANNs. The CM weights are determined with GA which its fitness function is minimizing the RMSE. Then, another GA specifies the final solution with object maximizing the global desirability. This algorithm was implemented on five case studies and the results represent the algorithm can get higher global desirability by repeating the runs and economic run number (ERN) depends on the MRO problem objective. ERN is ten for objective “Target”. This number for objectives which are mixture of minimization and maximization ERN is five. The repetition are continued until these ERN values have considerable increased in maximum GD with respect to average value of GD. More repetition from these ERN to forty five numbers cause a slight raise in maximum GD. |
| first_indexed | 2024-03-06T07:55:15Z |
| format | Article |
| id | upm.eprints-22878 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T07:55:15Z |
| publishDate | 2014 |
| publisher | Trans Tech Publications |
| record_format | dspace |
| spelling | upm.eprints-228782020-04-15T16:20:47Z http://psasir.upm.edu.my/id/eprint/22878/ Higher desirability in solving multiple response optimization problems with committee machine Golestaneh, Seyed Jafar Ismail, Napsiah Mohd Ariffin, Mohd Khairol Anuar Tang, Sai Hong Naeini, Hassan Moslemi Maghsoudi, Ali Asghar Firoozi, Zahra Many industrial problems need to be optimized several responses simultaneously. These problems are named multiple response optimization (MRO) and they can have different objectives such as Target, Minimization or Maximization. Committee machine (CM) as a set of some experts such as some artificial neural networks (ANNs) in combination with genetic algorithm (GA) is applied for modeling and optimization of MRO problems. In addition, optimization usually is done on Global Desirability (GD) function. Current article is a development for recent authors' work to determine economic run number for application of CM and GA in MRO problem solving. This study includes a committee machine with four different ANNs. The CM weights are determined with GA which its fitness function is minimizing the RMSE. Then, another GA specifies the final solution with object maximizing the global desirability. This algorithm was implemented on five case studies and the results represent the algorithm can get higher global desirability by repeating the runs and economic run number (ERN) depends on the MRO problem objective. ERN is ten for objective “Target”. This number for objectives which are mixture of minimization and maximization ERN is five. The repetition are continued until these ERN values have considerable increased in maximum GD with respect to average value of GD. More repetition from these ERN to forty five numbers cause a slight raise in maximum GD. Trans Tech Publications 2014 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/22878/1/Higher%20desirability%20in%20solving%20multiple%20response%20optimization%20problems%20with%20committee%20machine.pdf Golestaneh, Seyed Jafar and Ismail, Napsiah and Mohd Ariffin, Mohd Khairol Anuar and Tang, Sai Hong and Naeini, Hassan Moslemi and Maghsoudi, Ali Asghar and Firoozi, Zahra (2014) Higher desirability in solving multiple response optimization problems with committee machine. Applied Mechanics and Materials, 564. pp. 608-613. ISSN 1660-9336; ESSN: 1662-7482 https://www.scientific.net/AMM.564.608 10.4028/www.scientific.net/AMM.564.608 |
| spellingShingle | Golestaneh, Seyed Jafar Ismail, Napsiah Mohd Ariffin, Mohd Khairol Anuar Tang, Sai Hong Naeini, Hassan Moslemi Maghsoudi, Ali Asghar Firoozi, Zahra Higher desirability in solving multiple response optimization problems with committee machine |
| title | Higher desirability in solving multiple response optimization problems with committee machine |
| title_full | Higher desirability in solving multiple response optimization problems with committee machine |
| title_fullStr | Higher desirability in solving multiple response optimization problems with committee machine |
| title_full_unstemmed | Higher desirability in solving multiple response optimization problems with committee machine |
| title_short | Higher desirability in solving multiple response optimization problems with committee machine |
| title_sort | higher desirability in solving multiple response optimization problems with committee machine |
| url | http://psasir.upm.edu.my/id/eprint/22878/1/Higher%20desirability%20in%20solving%20multiple%20response%20optimization%20problems%20with%20committee%20machine.pdf |
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