Crossing weighted uncertainty scenarios assisted distribution-free metamodel-based robust simulation optimization
In practice, computer simulations cannot be perfectly controlled because of the inherent uncertainty caused by variability in the environment (e.g., demand rate in the inventory management). Ignoring this source of variability may result in suboptimality or infeasibility of optimal solutions. This p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Springer
2020
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| Online Access: | http://psasir.upm.edu.my/id/eprint/88308/1/ABSTRACT.pdf |
| _version_ | 1796981955410001920 |
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| author | Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah |
| author_facet | Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah |
| author_sort | Parnianifard, Amir |
| collection | UPM |
| description | In practice, computer simulations cannot be perfectly controlled because of the inherent uncertainty caused by variability in the environment (e.g., demand rate in the inventory management). Ignoring this source of variability may result in suboptimality or infeasibility of optimal solutions. This paper aims at proposing a new method for simulation–optimization when limited knowledge on the probability distribution of uncertain variables is available and also limited budget for computation is allowed. The proposed method uses the Taguchi robust terminology and the crossed array design when its statistical techniques are replaced by design and analysis of computer experiments and Kriging. This method ofers a new approach for weighting uncertainty scenarios for such a case when probability distributions of uncertain variables are unknown without available historical data. We apply a particular bootstrapping technique when the number of simulation runs is much less compared to the common bootstrapping techniques. In this case, bootstrapping is undertaken by employing original (i.e.,
non-bootstrapped) data, and thus, it does not result in a computationally expensive task. The applicability of the proposed method is illustrated through the Economic Order Quantity (EOQ) inventory problem, according to uncertainty in the demand rate and holding cost. |
| first_indexed | 2024-03-06T10:45:14Z |
| format | Article |
| id | upm.eprints-88308 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:45:14Z |
| publishDate | 2020 |
| publisher | Springer |
| record_format | dspace |
| spelling | upm.eprints-883082022-11-24T02:06:02Z http://psasir.upm.edu.my/id/eprint/88308/ Crossing weighted uncertainty scenarios assisted distribution-free metamodel-based robust simulation optimization Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah In practice, computer simulations cannot be perfectly controlled because of the inherent uncertainty caused by variability in the environment (e.g., demand rate in the inventory management). Ignoring this source of variability may result in suboptimality or infeasibility of optimal solutions. This paper aims at proposing a new method for simulation–optimization when limited knowledge on the probability distribution of uncertain variables is available and also limited budget for computation is allowed. The proposed method uses the Taguchi robust terminology and the crossed array design when its statistical techniques are replaced by design and analysis of computer experiments and Kriging. This method ofers a new approach for weighting uncertainty scenarios for such a case when probability distributions of uncertain variables are unknown without available historical data. We apply a particular bootstrapping technique when the number of simulation runs is much less compared to the common bootstrapping techniques. In this case, bootstrapping is undertaken by employing original (i.e., non-bootstrapped) data, and thus, it does not result in a computationally expensive task. The applicability of the proposed method is illustrated through the Economic Order Quantity (EOQ) inventory problem, according to uncertainty in the demand rate and holding cost. Springer 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/88308/1/ABSTRACT.pdf Parnianifard, Amir and Ahmad, Siti Azfanizam and Mohd Ariffin, Mohd Khairol Anuar and Ismail, Mohd Idris Shah (2020) Crossing weighted uncertainty scenarios assisted distribution-free metamodel-based robust simulation optimization. Engineering with Computers, 36 (1). 139 - 150. ISSN 0177-0667; ESSN: 1435-5663 https://link.springer.com/article/10.1007/s00366-018-00690-0 10.1007/s00366-018-00690-0 |
| spellingShingle | Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah Crossing weighted uncertainty scenarios assisted distribution-free metamodel-based robust simulation optimization |
| title | Crossing weighted uncertainty scenarios assisted distribution-free metamodel-based robust simulation optimization |
| title_full | Crossing weighted uncertainty scenarios assisted distribution-free metamodel-based robust simulation optimization |
| title_fullStr | Crossing weighted uncertainty scenarios assisted distribution-free metamodel-based robust simulation optimization |
| title_full_unstemmed | Crossing weighted uncertainty scenarios assisted distribution-free metamodel-based robust simulation optimization |
| title_short | Crossing weighted uncertainty scenarios assisted distribution-free metamodel-based robust simulation optimization |
| title_sort | crossing weighted uncertainty scenarios assisted distribution free metamodel based robust simulation optimization |
| url | http://psasir.upm.edu.my/id/eprint/88308/1/ABSTRACT.pdf |
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