ﮐﻨﺘﺮل زﻧﺠﯿﺮهﻫﺎی ﺗﺎﻣﯿﻦ ﺣﻠﻘﻪ ﺑﺴﺘﻪ در ﮐﺎرﺧﺎﻧﻪﻫﺎی ﻫﻮﺷﻤﻨﺪ ﺑﺎ در ﻧﻈﺮ ﮔﺮﻓﺘﻦ ﻋﻮاﻣﻞ ﻏﯿﺮﻗﻄﻌﯽ و ﻣﺨﺮب: روﯾﮑﺮد ﻧﻈﺮﯾﻪ ﺑﺎزیﻫﺎ

اﻣﺮوزه، زﻧﺠﯿﺮهﻫﺎی ﺗﺎﻣﯿﻦ ﺣﻠﻘﻪ ﺑﺴﺘﻪ1 در ﺻﻨﺎﯾﻊ ﺑﺎ ﻫﺪف ﮐﺎﻫﺶ ﻣﺼﺮف ﻣﻮاد اوﻟﯿﻪ ﺧﺎم و اﺳﺘﻔﺎده ﻣﺠﺪد از ﻣﺤﺼﻮﻻت، اﺳﺘﻘﺒﺎل ﭼﺸﻤﮕﯿﺮی داﺷﺘﻪ اﻧﺪ. ﺑﺪﯾﻦ ﺗﺮﺗﯿﺐ، ﻣﺪﯾﺮﯾﺖ اﯾﻦ زﻧﺠﯿﺮهﻫﺎ در ﺣﻮزهﻫﺎی ﻣﺨﺘﻠﻒ ﺣﺎﺋﺰ اﻫﻤﯿﺖ ﺧﻮاﻫﺪ ﺑﻮد. در اﯾﻦ زﻧﺠﯿﺮهﻫﺎ، ﻣﺤﺼﻮﻻت اﺳﺘﻔﺎده ﺷﺪه، ﺑﻪ ﻋﻨﻮان ﻣﻨﺎﺑﻊ اوﻟﯿﻪ ﺗﻮﻟﯿﺪ ﺑﻪ ﭼﺮﺧﻪ ﺑﺎزﻣﯽﮔﺮدﻧﺪ. اﯾﻦ زﻧﺠﯿﺮهﻫﺎ ﺑﻪ ﮐﺸﻮرﻫﺎ در ﺟﻬﺖ ﮐﺎﻫﺶ ﻣﺼﺮف ﻣﻨﺎﺑﻊ ﺧﺎم ﮐﻤﮏ ﮐﺮده و ﻫﻤﭽﻨﯿﻦ ﻓﺮﺻﺘﯽ ﺑﺮای ﺗﻮﻟﯿﺪﮐﻨﻨﺪﮔﺎن ﺧﻮاﻫﻨﺪ ﺑﻮد ﺗﺎ ﺑﺎ ﺑﺎزﻣﺼﺮف ﻣﻮاد اﺳﺘﻔﺎده ﺷﺪه، ﺳﻮدآوری را اﻓﺰاﯾﺶ دﻫﻨﺪ. ﺑﻪ ﻋﻠﺖ ﺗﺎﺛﯿﺮ اﯾﻦ زﻧﺠﯿﺮهﻫﺎ در ﺻﻨﺎﯾﻊ، ﺗﻮﺟﻪ ﻣﺤﻘﻘﺎن ﺑﻪ ﭘﮋوﻫﺶ در ﺣﻮزه ﻣﺪﯾﺮﯾﺖ اﯾﻦ دﺳﺘﻪ زﻧﺠﯿﺮهﻫﺎ ﺟﻠﺐ ﺷﺪه اﺳﺖ. در اﯾﻦ ﺗﺤﻘﯿﻖ، ﯾﮏ ﻣﻌﻤﺎری ﮐﻨﺘﺮﻟﯽ ﻣﺒﺘﻨﯽ ﺑﺮ ﻧﻈﺮﯾﻪ ﺑﺎزیﻫﺎ2 ﺑﺮای ﻣﺪﯾﺮﯾﺖ زﻧﺠﯿﺮهﻫﺎی ﺗﺎﻣﯿﻦ ﺣﻠﻘﻪ ﺑﺴﺘﻪ در ﺣﻀﻮر ﻋﻮاﻣﻞ ﻏﯿﺮﻗﻄﻌﯽ و ﻣﺨﺮب، ﻣﻌﺮﻓﯽ ﺷﺪه اﺳﺖ. ﺑﺪﯾﻦ ﻣﻨﻈﻮر، از ﯾﮏ ﮐﻨﺘﺮلﮐﻨﻨﺪه ﺗﻨﺎﺳﺒﯽ-اﻧﺘﮕﺮاﻟﯽ-ﻣﺸﺘﻘﯽ3 ﺑﺎ ﻗﺎﺑﻠﯿﺖ ﺗﻨﻈﯿﻢ ﺧﻮدﮐﺎر ورودیﻫﺎ ﺗﻮﺳﻂ ﻧﻈﺮﯾﻪ ﺑﺎزیﻫﺎ اﺳﺘﻔﺎده ﺷﺪه اﺳﺖ. ﺑﺎ اﯾﺠﺎد ﯾﮏ ﺑﺎزی ﺑﯿﻦ ورودیﻫﺎی اﯾﻦ ﮐﻨﺘﺮلﮐﻨﻨﺪه و ﯾﺎﻓﺘﻦ ﻧﻘﻄﻪ ﺗﻌﺎدل ﺑﺎزی ﺗﻌﺎدل ﻧَﺶ4 ، ﻣﯽﺗﻮان ﺑﻬﺘﺮﯾﻦ وﺿﻌﯿﺖ ﮐﻨﺘﺮلﮐﻨﻨﺪه را ﻣﺸﺨﺺ ﻧﻤﻮد. ﻧﺘﺎﯾﺞ ﺣﺎﺻﻞ ﻧﺸﺎن ﻣﯽ دﻫﺪ ﮐﻪ ﮐﻨﺘﺮلﮐﻨﻨﺪه ﭘﯿﺸﻨﻬﺎدی ﻣﯽ ﺗﻮاﻧﺪ در زﻧﺠﯿﺮه ﺗﺎﻣﯿﻦ ﺣﻠﻘﻪ ﺑﺴﺘﻪ، ﺑﺎ ﺗﻨﻈﯿﻢ ﺧﻮدﮐﺎر ورودیﻫﺎ، ﮐﺎراﯾﯽ ﺧﻮد را ﺑﻬﯿﻨﻪ ﻧﻤﻮده و در ﻣﺪﯾﺮﯾﺖ زﻧﺠﯿﺮه ﻫﺎی ﻓﻮق ﮐﺎرآﻣﺪ واﻗﻊ ﺷﻮد.

closed-loop supply chain control in smart factories considering uncertainty and disruption: a game theory approach

due to the increasing use of closed-loop supply chains clscs in industry scopes in order to optimize raw material usage and reuse of end-of-life or used products, clsc management is very necessary. used products return to production cycles as production resources in clsc processes. thus, clsc helps countries to use fewer raw materials for manufacturing and brings an opportunity for manufacturers to reuse end-of-life products, so that they can increase their overcome and decrease the use of natural resources simultaneously. due to the impact of clsc on industries, clsc control is an interesting field of research. in this paper, a new game theory-based architecture for controlling clsc considering uncertainty will be introduced. for this purpose, a smart proportional-integral-derivative pid controller will be used which automatically tunes itself using the game theory method. thus, creating a game with controller gains and searching for the equilibria point of the game, makes the best state for the controller. so that the controller could act rationally in clsc and tune itself to optimize its performance. the optimized reaction of the controller used in this model would help the clsc management system.