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Optimizing a fuzzy inventory model using multithreading and artificial neural network under inflation

Title
Optimizing a fuzzy inventory model using multithreading and artificial neural network under inflation
Other Titles
인플레이션에서 멀티 스레드와 인공 신경망을 적용한 퍼지 재고 모형 최적화
Author
Arijit Sarkar
Alternative Author(s)
아리짓 사카
Advisor(s)
Biswajit Sarkar
Issue Date
2017-08
Publisher
한양대학교
Degree
Master
Abstract
The application of neural network is spread-out throughout the field of optimization. Within neural network diagram, the optimization with multithreading has gained a lot of popularity. This proposed research introduces the effect of neural network with multithreading in a basic inventory model under uncertain environment. This study develops multi-items in a multi-period inventory model under the effects of time value of money, uncertain demands and inflation. Fuzzy models are based on more realistic approach on data. Traditionally, for the sake of simplicity most of the time researchers considers demand as constant. But in reality, it is very difficult to determine the exact amount of future demand. Therefore, results, generated by constant terms, estimate of the total cost but may or may not be same as the value observed in reality. Therefore, in order to obtain a more realistic idea about the cost, this paper discusses about an uncertain demand and it is applied to a bi-objective multi-product inventory model. The total inventory cost is minimized with respect to minimum space required for storage for finding an optimal balanced range by using concepts of multithreading and artificial neural networks. Multithreading is used to generate multiple threads, where each thread is a possible solution. Each of these threads acts as a node in a neural network and then after a comparison procedure the final result set is generated with best fits. Some numerical examples are given to illustrate the results. The comparative study with other existing algorithm is conducted. Results show that this model gives reduced cost with reduced time.
URI
http://hdl.handle.net/20.500.11754/33382http://hanyang.dcollection.net/common/orgView/200000431014
Appears in Collections:
GRADUATE SCHOOL[S](대학원) > INDUSTRIAL MANAGEMENT ENGINEERING(산업경영공학과) > Theses (Ph.D.)
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