Application of fuzzy hierarchical analysis in decision-making approach for selection of storage position-a case study of CRC

• Main Authors: Chun-Hung Ou, 歐俊宏
• Other Authors: Chiang Kao
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/08283273168711851553

碩士 === 國立成功大學 === 資訊管理研究所 === 92 === ___________________Abstract In a raw material warehousing system, storage space and storage/retrieval machine are two limiting factors, which become an important issue for the operation of warehousing system in fulfilling the criteria of waiting time and storage/retrieval speed. For an open storage space and bulk material, characterized by substantial amount and difficulty in precise quantification, manual operation becomes the primary option in the selection of storage position. However, there exists a lot of fuzzy information in the manual selection of storage position. How to convert this fuzzy verbal information into useful data becomes an important issue. In this study, fuzzy hierarchical analysis was used to develop a decision-making model with minimal piles. Category of raw material, producing country, space used in the storage field, operation state of equipment and utilization rate of raw material were also considered. Finally, this fuzzy decision-making model was examined to explore the differences of results obtained by fuzzy and crisp methodologies. Through the case study of China Steel Corporation (CSC), current operation of storage field of CSC was studied and fuzzy comprehensive evaluation revealed that the selection of storage position simulated by fuzzy multi-criteria was superior to the conventional decision-making approach by manual operation at the same time points. At a variety of time points, the simulated results obtained from approaches based on different fuzzy theories were all superior to the conventional approach and that based on simple data. In this study, decision objectives with a difference of <20% with the optimal triangle fuzzy number were incorporated into the consideration during the selection of storage position. This would make the unfuzzy decision-making process based on fuzzy theory with unquantifiable rules more completed. Our study results can be a reference for academic studies on decision making using fuzzy and crisp numbers.