مدل بهينه سازي چند دوره اي تخصيص - مسيريابي پرسنل پزشكي به منظور ارائه خدمات سلامت

A Multi Period Routing and Scheduling optimization Model for Home health Care Problem

ﺳﺮوﯾﺲدﻫﯽ ﺧﺪﻣﺎت ﭘﺰﺷﮑﯽ در ﻣﻨﺰل از اﻫﻤﯿﺖ ﺑﺎﻻﯾﯽ در ﺟﻮاﻣﻊ اﻣﺮوزي ﺑﺮﺧﻮردار اﺳﺖ. در اﮐﺜـﺮ ﻣﻮﺳﺴـﺎت ﻓﻌﺎل اﯾﻦ ﺣﻮزه در اﯾﺮان از دﯾﺪﮔﺎه ﺳﻨﺘﯽ ﺑﺮاي ﺑﺮﻧﺎﻣﻪ رﯾﺰي و ﻣـﺪﯾﺮﯾﺖ ﭘﺮﺳـﻨﻞ ﭘﺰﺷـﮑﯽ و ﺗﻌﯿـﯿﻦ ﺗﺮﺗﯿـﺐ وﯾﺰﯾـﺖ ﺑﯿﻤﺎران اﺳﺘﻔﺎده ﻣﯽ ﺷﻮد ﮐﻪ اﯾﻦ اﻣﺮ در ﻏﺎﻟﺐ اوﻗﺎت ﺑﺎﻋﺚ اﻓﺰاﯾﺶ ﻫﺰﯾﻨﻪ ﻫﺎ و ﮐﺎﻫﺶ رﺿﺎﯾﺖ ﺑﯿﻤﺎران ﻣـﯽ ﮔـﺮدد. در اﯾﻦ ﺗﺤﻘﯿﻖ ﯾﮏ ﻣﺪل ﺑﺮﻧﺎﻣﻪ رﯾﺰي رﯾﺎﺿﯽ ﭼﻨﺪ دوره اي ﻣﺴﯿﺮﯾﺎﺑﯽ- ﺗﺨﺼﯿﺺ ﭘﺮﺳﻨﻞ ﭘﺰﺷﮑﯽ ﺑﻪ ﻣﻨﻈﻮر وﯾﺰﯾﺖ ﺑﯿﻤﺎران و اراﺋﻪ ﺧﺪﻣﺎت ﭘﺰﺷﮑﯽ ﺑﻪ آﻧﻬﺎ ﺑﺮرﺳﯽ ﺷﺪه اﺳﺖ. در ﻧﻈﺮ ﮔﺮﻓﺘﻦ ارﺗﺒﺎط و ﻋﺪم ارﺗﺒﺎط وﯾﺰﯾﺖ ﻫﺎي ﯾـﮏ ﺑﯿﻤﺎر ﺑﻪ ﯾﮑﺪﯾﮕﺮ، ﭼﻨﺪ ﻣﺒﺪاي ﻓﺮض ﮐﺮدن ﻣﺪل در ﮐﻨﺎر ﭼﻨﺪ دوره اي ﺑﻮدن آن از ﺟﻤﻠﻪ ﻧﻮآوري ﻫﺎي اﯾﻦ ﻣﻘﺎﻟـﻪ اﺳﺖ. ﻫﺪف ﻣﺪل ﭘﯿﺸﻨﻬﺎدي ﺣﺪاﻗﻞ ﺳﺎزي ﻫﺰﯾﻨﻪ ﻫﺎي ﮐﻞ ﻣﻮﺳﺴﻪ اﺳﺖ. ﻣﺪل در ﻣﻘﯿـﺎس ﮐﻮﭼـﮏ ﺑـﺎ ﻧـﺮم اﻓـﺰار ﮔﻤﺰ ﺣﻞ ﺷﺪه اﺳﺖ. ﺑﺮاي ﺣﻞ ﻣﺪل در ﻣﻘﯿﺎس ﺑﺰرگ اﻟﮕـﻮرﯾﺘﻢ ﺗﻮﺳـﻌﻪ داده ﺷـﺪه ﺟﺴـﺘﺠﻮي ﻫﻤﺴـﺎﯾﮕﯽ ﻣﺘﻐﯿـﺮ ﭘﯿﺸﻨﻬﺎد ﺷﺪه اﺳﺖ و ﻋﻤﻠﮑﺮد آن ﺑﺎ دو اﻟﮕﻮرﯾﺘﻢ ﺷﺒﯿﻪ ﺳﺎزي ﺗﺒﺮﯾﺪ و ﺳﯿﺴﺘﻢ ﮐﻠﻮﻧﯽ ﻣﻮرﭼﮕﺎن ﻣﻘﺎﯾﺴﻪ ﺷﺪه اﺳﺖ. ﻧﺘﺎﯾﺞ ﻧﺸﺎن از ﮐﺎﻫﺶ ﻫﺰﯾﻨﻪ ﻫﺎ و ﻋﻤﻠﮑﺮد ﻣﻨﺎﺳﺐ اﻟﮕﻮرﯾﺘﻢ ﭘﯿﺸﻨﻬﺎدي دارد.

Home health care services have a key importance in modern societies. Most organizations working in this area in Iran use the traditional procedure to plan and manage medical staff and determine the arrangement of visiting patients. This procedure often increases costs and reduces the satisfaction of patients. In this paper, a multi-period routing and scheduling model is proposed in order to visit patients and provide them medical services. Considering both dependency and independence of a patient's visits with each other, assuming the model as multi-depot as well as multi period are some innovations of this study. The main purpose of the proposed model is to reduce total costs of home health care organization. Model has been solved in small scale by GAMS software. To solve the model in large scale, developed Variable neighborhood search is proposed and compared with simulated annealing algorithm and ant colony system. Results show that costs are decreased and the proposed algorithm has better performance.