طراحي سيستم پشتيبان تصميم به منظور پيش بيني تقاضا جهت طراحي شبكه پويا پايدار در شرايط عدم قطعيت و تأثير آن بر توجيه پذيري اقتصادي

Design of Decision Support System to Forecast Demand for Dynamic Network Design Based on Uncertainty and its Impact on Economic Justification

ﺑﻪ ﺣﺪاﻗﻞ رﺳﯿﺪن ﻫﺰﯾﻨﻪﻫﺎي زﻧﺠﯿﺮه ﺗﺄﻣﯿﻦ ﺑﻪ ﻋﻨﻮان ﯾﮑﯽ از ﻣﺴﺎﺋﻞ ﺿﺮوري در ﻓﻌﺎﻟﯿﺖﻫﺎي ﻣﺮﺗﺒﻂ ﺑﺎ ﭘﺸﺘﯿﺒﺎﻧﯽ ﺳﯿﺴﺘﻢﻫﺎي ﺗﻮﻟﯿﺪي و ﺧﺪﻣﺎﺗﯽ، ﺳﯿﺴﺘﻢﻫﺎي ﺑﺮﻧﺎﻣﻪرﯾﺰي ﻣﺎﻟﯽ، ﻓﻌﺎﻟﯿﺖﻫﺎي ﻣﺮﺑﻮط ﺑﻪ ﺑﺎزارﯾﺎﺑﯽ و ﻓﺮوش و ﻗﯿﻤﺖ ﺗﻤﺎم ﺷﺪه ﻣﺤﺼﻮﻻت ﺑﻪ ﭼﮕﻮﻧﮕﯽ ﻣﺪﯾﺮﯾﺖ زﻧﺠﯿﺮه ﺗﺄﻣﯿﻦ روشﻫﺎﯾﯽ ﮐﻪ ﺑﺮاي ﯾﮑﭙﺎرﭼﻪﺳﺎزي ﻣﺆﺛﺮ ﺗﺄﻣﯿﻦﮐﻨﻨﺪﮔﺎن، ﺗﻮﻟﯿﺪﮐﻨﻨﺪﮔﺎن، اﻧﺒﺎرﻫﺎ و ﻓﺮوﺷﮕﺎهﻫﺎ ﺑﻪ ﮐﺎر ﻣﯽرود، ﺑﺴﺘﮕﯽ دارد ﺗﺎ ﻫﺰﯾﻨﻪﻫﺎي ﮐﻞ زﻧﺠﯿﺮه ﺗﺄﻣﯿﻦ ﺑﻪ ﺣﺪاﻗﻞ ﺑﺮﺳﺪ و ﻫﻤﭽﻨﯿﻦ ﻧﯿﺎز ﻣﺸﺘﺮﯾﺎن ﺑﺎ ﺳﻄﺢ ﺧﺪﻣﺖرﺳﺎﻧﯽ ﺑﺎﻻﯾﯽ ﺑﺮآورده ﺷﻮد. در اﯾﻦ ﭘﮋوﻫﺶ در راﺳﺘﯽ ﺣﺪاﻗﻞ ﻧﻤﻮدن ﻫﺰﯾﻨﻪﻫﺎي زﻧﺠﯿﺮه ﺗﺄﻣﯿﻦ و ﺑﻪ ﻣﻨﻈﻮر ﺑﺮﻧﺎﻣﻪرﯾﺰي و ﻃﺮاﺣﯽ ﺷﺒﮑﻪ زﻧﺠﯿﺮه ﺗﺎﻣﯿﻦ ﭘﻮﯾﺎ در ﺷﺮاﯾﻂ ﻋﺪم ﻗﻄﻌﯿﺖ از اﺑﺰار ﭘﯿﺶ ﺑﯿﻨﯽ ﺑﺎ اﺳﺘﻔﺎده از ﺷﺒﮑﻪ ﻋﺼﺒﯽ ﻣﺼﻨﻮﻋﯽ ﭘﺮداﺧﺘﻪ ﺷﺪهاﺳﺖ. ﯾﮑﯽ از ﻣﻬﻤﺘﺮﯾﻦ ﻣﻮارد رﻋﺎﯾﺖ ﺷﺪه در اﯾﻦ ﭘﮋوﻫﺶ اﺳﺘﻔﺎده از ﻣﺘﺪوﻟﻮژيﻫﺎي ﻫﻮش ﻣﺼﻨﻮﻋﯽ ﻣﺎﻧﻨﺪ Grid Clustering, Subtractive Partitioning, FCM ﻣﯽﺑﺎﺷﺪ، ﮐﻪ ﺑﻪ ﻣﻨﻈﻮر ﮐﺸﻒ اﻟﮕﻮﻫﺎ و رواﺑﻂ ﺑﻨﯿﺎدي و ﺗﮑﻨﯿﮑﺎل ﻣﻮﺟﻮد در دادهﻫﺎي ﺗﺎرﯾﺨﯽ اﺳﺘﻔﺎده ﺷﺪه اﺳﺖ. در اﯾﻦ راﺳﺘﺎ ﺑﻪ اراﺋﻪ ﯾﮏ ﺷﺒﮑﻪ ﻋﺼﺒﯽ ﻣﺼﻨﻮﻋﯽ ﭼﻨﺪ ﻻﯾﻪ ﻓﺎزي اﺳﺘﻨﺘﺎﺟﯽ ﻣﺒﺘﻨﯽ ﺑﺮ ژﻧﺘﯿﮏ ﺟﻬﺖ ﺟﻠﻮﮔﯿﺮي از ﻏﯿﺮﺗﻮﺟﯿﻪ ﭘﺬﯾﺮي ﻓﻨﯽ و اﻗﺘﺼﺎدي ﺣﻞ و اﺟﺮا ﭘﺮداﺧﺘﻪ ﺷﺪه اﺳﺖ. ﻣﺪل ﭘﺎﯾﻪ اﯾﻦ ﻣﻘﺎﻟﻪ ﮐﻪ ﺗﻮﺳﻂ ﻣﺤﻘﻖ اراﺋﻪ ﺷﺪه اﺳﺖ ﺑﻪ ﺑﺮﻧﺎﻣﻪرﯾﺰي اﺳﺘﻮار و ﭼﻨﺪ دورهاي ﺑﺮاي ﺣﺎﻟﺖ ﭼﻨﺪ ﻣﺤﺼﻮﻟﯽ در ﺷﺮاﯾﻂ ﻋﺪم ﻗﻄﻌﯿﺖ ﻣﯽﺑﺎﺷﺪ.

Minimize supply chain costs as one of the essential issues in support activities such as financial planning systems,How to manage supply chain A set of ways to integrate Effective suppliers, manufacturers, warehouses and stores used to minimize total supply chain costs and meet customer service needs with a high level of service. In this study, the design of a robust cement supply chain dynamic network model was designed to reduce supply chain management costs after a crisis. Principal and efficient design of cement grid infrastructures, given the strong demand fluctuations at different times of the year, can significantly reduce financial costs on the one hand and reduce the potential for high-speed, high-cost corruption by correct prediction. Other leads.From the following tool The nose has been analyzed using artificial neural networks. The purpose of this study is to use artificial intelligence methodologies such as Grid Clustering, Subtractive Partitioning, FCM to explore fundamental and technical patterns and relationships in historical data. Used. To this end, a genetically-based inference fuzzy multilayer fuzzy neural network is introduced to prevent technical and economic unpredictability. The basic model of this paper presented by the researcher is a robust and multi-periodic planning for multi-product state under uncertainty.