19740

۱۹۷۴۰

بهينه‌سازي هزينه موج‌شكن‌هاي سنگريزه‌اي با استفاده از مدل GAMS و الگوريتم ژنتيك

كارشناسي ارشد

مهندسي سواحل

93-94

اسفند ۱۳۹۴

دكتر عباس يگانه بختياري - دكتر محمدحسين كاظمي نژاد

عمران

ﻣﻮجﺷـﮑﻦ از ﺟﻤﻠﻪ ﺳـﺎزهﻫﺎي ﺳـﺎﺣﻠﯽ ﭘﺮﻫﺰﯾﻨﻪ و ﺑﺴـﯿﺎر ﻣﻬﻢ اﺳﺖ. ﻣﻮجﺷﮑﻦ ﺳﻨﮕﺮﯾﺰهاي راﯾﺞﺗﺮﯾﻦ ﻧﻮع اﯾﻦ ﺳـﺎزهﻫﺎ در ﺳـﻄﺢ دﻧﯿﺎ ﺑﻮده ﮐﻪ در ﮐﺸـﻮر اﯾﺮان ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ ﺷﺮاﯾﻂ ﻣﻨﺎﺳﺐ اﻋﻤﺎق و وﺟﻮد ﻣﺼﺎﻟﺢ ﻣﺮﺗﺒﻂ ﺟﺰو اﺻـﻠﯽﺗﺮﯾﻦ ﮔﺰﯾﻨﻪﻫﺎ ﺟﻬﺖ ﺳـﺎﺧﺖ در ﺑﻨﺎدر اﺳﺖ. ﻫﻤﺎﻧﻄﻮر ﮐﻪ از ﻧﺎم ﻣﻮج ﺷﮑﻦ ﻫﺎ ﻣﺸﺨﺺ اﺳﺖ ﻫﺪف اﺻﻠﯽ اﺳﺘﻔﺎده از اﯾﻦ ﺳﺎزه ﻫﺎ ﻣﻬﺎر و اﺳﺘﻬﻼك ﻧﯿﺮوي ﻣﻮج و در ﻧﺘﯿﺠﻪ ﺣﻔﻆ آراﻣﺶ و اﻣﻨﯿﺖ ﺣﻮﺿﭽﻪ ﻫﺎي ﺑﻨﺎدر از ﮔﺰﻧﺪ اﯾﻦ ﻧﯿﺮوي ﻋﻈﯿﻢ ﻃﺒﯿﻌﯽ اﺳـﺖ. ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ اﯾﻦ ﻣﻮﺿـﻮع ﮐﻪ ﺳﺎﺧﺖ ﻣﻮجﺷﮑﻦ ﻋﻤﺪه ﻫﺰﯾﻨﻪﻫﺎي ﻣﺼﺮﻓﯽ ﯾﮏ ﺑﻨﺪر را ﺗﺸـﮑﯿﻞ ﻣﯽدﻫﺪ، ﺑﻬﯿﻨﻪﺳـﺎزي ﻣﻮجﺷﮑﻦﻫﺎ ﻣﯽﺗﻮاﻧﺪ در ﺻﺮﻓﻪﺟﻮﯾﯽ ﻫﺰﯾﻨﻪﻫﺎي ﻧﻬﺎﯾﯽ ﮐﻤﮏ ﻧﻤﺎﯾﺪ. در ﻃﺮاﺣﯽ ﻣﻮجﺷــﮑﻦﻫﺎي ﺳــﻨﮕﺮﯾﺰهاي درﻧﻈﺮﮔﯿﺮي ﻋﻮاﻣﻞ و ﻣﻮدﻫﺎي ﺧﺮاﺑﯽ ﺑﺼــﻮرت ﻫﻤﺰﻣﺎن ﮐﺎري ﭘﯿﭽﯿﺪه اﺳﺖ. ﺑﻨﺎﺑﺮاﯾﻦ دﺳﺘﯿﺎﺑﯽ ﺑﻪ ﯾﮏ ﻃﺮح ﺑﻬﯿﻨﻪ ﻣﺴﺘﻠﺰم اﺳﺘﻔﺎده از ﻓﻦﻫﺎي ﻣﺨﺘﻠﻒ ﺑﻬﯿﻨﻪﺳﺎزي ﺑﺮاي ﺳﺮﻋﺖ و دﻗﺖ ﺑﺨﺸﯿﺪن ﺑﻪ ﻓﺮآﯾﻨﺪ ﻃﺮاﺣﯽ اﺳﺖ. در اﯾﻦ ﭘﮋوﻫﺶ ﺑﺎ اراﺋﻪ ﻣﺪل ﺑﻪ ﻃﺮاﺣﯽ ﺑﻬﯿﻨﻪ ﻣﻮجﺷــﮑﻦﻫﺎي ﺳــﻨﮕﺮﯾﺰهاي ﭘﺮداﺧﺘﻪﺷــﺪهاﺳــﺖ. در ﻣﻄﺎﻟﻌﺎت ﮔﺬﺷـﺘﻪ ﻣﻮجﺷـﮑﻦﻫﺎي ﻣﻮرد ﺑﺮرﺳﯽ از ﻧﻮع ﺳﻨﮕﺮﯾﺰهاي ﻧﺒﻮده و ﯾﺎ ﻧﺘﺎﯾﺞ ﻗﺎﺑﻠﯿﺖ ﺑﺮرﺳﯽ و اﺳﺘﻔﺎده ﺑﺮاي ﻣﻮارد ﻣﺸــﺎﺑﻪ داﺧﻠﯽ ﻧﺪاﺷــﺘﻨﺪ ﺑﻨﺎﺑﺮاﯾﻦ ﺑﺮاي ﻧﺰدﯾﮏ ﺷــﺪن ﻧﺘﺎﯾﺞ ﺑﺎ ﺻــﻨﻌﺖ ﺳــﺎﺧﺖ ﻣﻮجﺷــﮑﻦﻫﺎ در ﮐﺸــﻮر از دو ﻣﻮجﺷـــﮑﻦ ﻣﻮﺟﻮد ﺑﻪ ﻋﻨﻮان ﻧﻤﻮﻧﻪ اﺳـــﺘﻔﺎده ﺷـــﺪهاﺳـــﺖ. ﻣﺪلﺳـــﺎزي ﺑﺎ اﻟﮕﻮرﯾﺘﻢ ژﻧﺘﯿﮏ و ﻣﺪل GAMS اﻧﺠﺎمﮔﺮﻓﺘﻪاﺳـﺖ. ﻣﻮدﻫﺎي ﺧﺮاﺑﯽ ﻣﺮﺗﺒﻂ ﺑﺎ ﭘﺎﯾﺪاري ﻻﯾﻪ آرﻣﻮر، ﭘﺎﯾﺪاري ﭘﻨﺠﻪ ﻣﻮجﺷـﮑﻦ و ﺳﺮرﯾﺰي ﺑﻪ ﻋﻨﻮان ﻗﯿﻮد ﻃﺮاﺣﯽ اﻧﺘﺨﺎب ﺷـﺪهاﻧﺪ. در ﺗﻤﺎﻣﯽ ﻣﺮاﺣﻞ ﺳﻌﯽ ﺷﺪهاﺳﺖ ﮐﻪ رواﺑﻂ و ﻣﻌﯿﺎرﻫﺎي ﺗﺠﺮﺑﯽ و ﺑﻮﻣﯽ ﻃﺮاﺣﯽ رﻋﺎﯾﺖ ﺷﻮﻧﺪ ﮐﻪ ﻧﺘﺎﯾﺞ ﻧﻬﺎﯾﯽ ﻗﺎﺑﻞ اﺳﺘﻔﺎده ﺑﺮاي ﺻﻨﻌﺖ ﺳﺎﺧﺖوﺳﺎز ﻣﻮجﺷﮑﻦﻫﺎي ﺳﻨﮕﺮﯾﺰهاي در داﺧﻞ ﮐﺸﻮر ﺑﺎﺷﺪ. ﭘﺲ از ﺑﺮرﺳﯽ و ﻣﻘﺎﯾﺴﻪ ﻧﺘﺎﯾﺞ ﺑﺪﺳﺖ آﻣﺪه از ﻣﺪلﺳﺎزي ﺑﺎ ﻃﺮحﻫﺎي ﻓﻌﻠﯽ اﺟﺮا ﺷﺪه، اﯾﻨﮕﻮﻧﻪ ﻣﺸﺨﺺ ﺷﺪ ﮐﻪ اﻟﺰاﻣﯽ ﺑﺮاي اﺳـﺘﻔﺎده از راهﺣﻞﻫﺎي ﻣﺪلﺳﺎزي ﻧﺮماﻓﺰاري ﺑﺮاي ﻣﻮجﺷﮑﻦﻫﺎﯾﯽ ﮐﻪ ﺗﺤﺖ ﺗﺎﺛﯿﺮ ﺷﺮاﯾﻂ ﻣﺴﺎﻋﺪ از دﯾﺪ ﺳـﺎزهاي ﻫﺴﺘﻨﺪ، ﻧﺎﺳﺖ. در واﻗﻊ ﭘﯿﺸﻨﻬﺎد ﻣﯽﺷﻮد ﮐﻪ ﺑﺮاي ﻣﻮجﺷﮑﻦﻫﺎي ﺳﻨﮕﺮﯾﺰهاي ﮐﻪ ﭼﺎﻟﺶ ﺳﺎزهاي دارﻧﺪ و ﻋﻮاﻣﻞ ﺗﺎﺛﯿﺮﮔﺬار در ﭘﺎراﻣﺘﺮﻫﺎي ﻃﺮاﺣﯽ آﻧﻬﺎ ﺑﺤﺮاﻧﯽﺗﺮ ﻫﺴﺘﻨﺪ، از اﯾﻨﮕﻮﻧﻪ راهﺣﻞﻫﺎ اﺳﺘﻔﺎده ﺷﻮد. ﻧﺘﺎﯾﺞ ﺑﺪﺳـﺖ آﻣﺪه از اﯾﻦ ﭘﮋوﻫﺶ ﻧﺸﺎن ﻣﯽدﻫﺪ ﮐﻪ اﺳﺘﻔﺎده از روشﻫﺎي ﺑﻬﯿﻨﻪﺳﺎزي ﻣﺬﮐﻮر ﺑﻪ ﺟﺎي روش ﻣﺘﺪاول ﻃﺮاﺣﯽ، ﻣﯽﺗﻮاﻧﺪ ﺑﯿﻦ 4 ﺗﺎ 24 درﺻﺪ ﻫﺰﯾﻨﻪﻫﺎي ﺳﺎﺧﺖ ﻣﻮجﺷﮑﻦﻫﺎي ﺳﻨﮕﺮﯾﺰهاي را ﮐﺎﻫﺶ دﻫﺪ. واژهﻫﺎي ﮐﻠﯿﺪي: ﻣﻮجﺷﮑﻦ ﺳﻨﮕﺮﯾﺰهاي، ﺑﻬﯿﻨﻪﺳﺎزي ﻫﺰﯾﻨﻪ، اﻟﮕﻮرﯾﺘﻢ ژﻧﺘﯿﮏ، GAMS، ﻣﻮد ﺧﺮاﺑﯽ

1397/08/01

Optimal Cost Design of Rubble Mound Breakwater Using GAMS and GA

3/7/2016 12:00:00 AM

Breakwaters are most important and also more expensive of coastal structures. Rubble mound breakwaters are most common type of this structure in the world. Due to depth of Persian Gulf waters in the near of the coastlines of Iran and local construction conditions such as material availability and construction machinery limitation, the rubble mound breakwater is one of the main options to build in ports and harbor. The main goal of this structure is wave power's depreciation and thus protect of the ports leeward, so optimization can take into account to minimize the total cost. The breakwater design process is complex. The process should integrate the technical aspects with environmental, economic and other factors together. As technical aspects, design method should consider several failure modes, constraints and requirements simultaneously, so achieving to this objective is very hard. The result of the geometry optimization maybe minimizes the total cost of the rubble mound breakwater with satisfying safety index and probability of failures. In this case, software optimization solutions such as GA (Genetic Algorithms) and GAMS (General Algebraic Modelling System) help to perform economic results. Armor stability, toe stability and overtopping have been considered as failure modes. Bounds of variables and other requirements have been considered in accordance with common codes, standards and practical design criteria. In this paper, each optimization methods have been developed then have been applied to two case studies, which were constructed and are operating in the Persian Gulf. In the last part, the results have been compared to conventional methods. Keywords: rubble mound breakwater, cost optimization, Genetic Algorithms, GAMS, failure modes