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توسعه یک مدل ریاضی مکانیابی- موجودی در طراحی شبکه لجستیک یکپارچه مستقیم/ معکوس تحت عدم قطعیت تقاضا و برگشتی با سطوح ظرفیت چندگانه | ||
مدیریت زنجیره تأمین | ||
مقاله 3، دوره 23، شماره 72، آذر 1400، صفحه 23-39 اصل مقاله (507.88 K) | ||
نوع مقاله: پژوهشی | ||
نویسندگان | ||
مهدی سیف برقی* 1؛ مهدی کربلایی اسماعیلی2 | ||
1گروه مهندسی صنایع، دانشکده مهندسی، دانشگاه الزهرا، دانشکده فنی، تهران، ایران | ||
2گروه مهندسی صنایع، دانشکده مهندسی صنایع و مکانیک، دانشگاه آزاد اسلامی، شعبه قزوین، قزوین، ایران | ||
تاریخ دریافت: 25 مرداد 1400، تاریخ بازنگری: 07 بهمن 1400، تاریخ پذیرش: 09 بهمن 1400 | ||
چکیده | ||
اﻣﺮوزه ﻣﺤﯿﻂ ﺗﺠﺎری رﻗﺎﺑﺘﯽ ﻣﻨﺠﺮ ﺑﻪ ﻫﻤﮑﺎری ﻓﺰاﯾﻨﺪه ﻣﯿﺎن شرکتها بهعنوان اﻋﻀﺎی شبکه زﻧﺠﯿﺮه تأمین شده اﺳﺖ. در اﯾﻦ زﻣﯿﻨﻪ، طراحی شبکه ﻟﺠﺴﺘﯿﮏ زنجیره تأمین ﺑـﺎ ﺗﻮﺟـﻪ ﺑـه ﺗﺄﺛﯿﺮ آن بر کارایی و ﭘﺎﺳﺨﮕﻮﯾﯽ زﻧﺠﯿﺮه از موضوعات مهم استراتژیک بهشمار میرود. ﻋﻼوهﺑﺮ اﯾﻦ، در سالهای اﺧﯿﺮ ﺗﻮﺟﻪ ﺑﻪ ﻣﺴـﺎﺋﻞ زیستمحیطی، اﻟﺰاﻣﺎت ﻗﺎﻧﻮﻧﯽ و نیز منافع اﻗﺘﺼـﺎدی توجه خاصی بر لجستیک معکوس صورت گرفته است. در این مقاله ﺑـﻪ اراﺋﻪ ﯾﮏ ﻣﺪل مکانیابی- موجودی و از نوع برنامهریزی ﺧﻄﯽ ﻋﺪد ﺻـﺤﯿﺢ آﻣﯿﺨﺘـﻪ احتمالی برای طراحی ﯾﮑﭙﺎرﭼـﻪ ﺷـﺒﮑﻪ ﯾـﮏ زنجیره تأمین حلقه بسته ﭼﻨﺪ کالایی و چند دورهای با در نظر گرفتن سطوح ظرفیت چندگانه پرداخته میشود. همچنین برای انطباق شبکه لجستیک مورد نظر با دنیای واقعی، مقدار تقاضای مشتریان و بالطبع مقدار برگشتی تحت عدم قطعیت و بهصورت تصادفی در نظر گرفته شدهاند. با توجه به اینکه مسئله مکانیابی تسهیلات با ظرفیت محدود در این تحقیق بهدستة مسائل سخت تعلق دارد، لذا برای حل آن به ارائه دو روش فرا ابتکاری مبتنیبر الگوریتم زنبورها و الگوریتم ژنتیک پرداخته و مقایسه جوابهای این دو روش براساس مسائل عددی طراحی شده صورت گرفته است. از نظر مقدار تابع هدف، عملکرد الگوریتم ژنتیک بهطور متوسط 6/11درصد پایینتر از زنبور عسل بوده و از منظر زمان حل عملکرد الگوریتم زنبور عسل به میزان قابل ملاحظهای (به طور متوسط نزدیک به 5 برابر) پایینتر از الگوریتم ژنتیک است. | ||
کلیدواژهها | ||
زنجیره تأمین حلقه بسته؛ طراحی شبکه؛ عدم قطعیت؛ الگوریتم ژنتیک؛ الگوریتم زنبور عسل | ||
عنوان مقاله [English] | ||
A Mathematical Location-Inventory Model for Designing a Forward /Backward Logistic Network under Demand and Return Uncertainty with Multiple Capacity Levels | ||
نویسندگان [English] | ||
Mehdi Seifbarghy1؛ Mehdi Karbalaei Esmaeili2 | ||
1Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran | ||
22Department of Industrial Engineering, Faculty of Mechanical and Industrial Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran | ||
چکیده [English] | ||
Today, the competitive business environment has led to increasing cooperation among companies as the members of supply chain networks. In this area, the supply chain logistics network design is an important subject due to its effect on the responsiveness and efficiency. Over the past few years, due to environmental issues, their legal requirements and economic benefits, great attention has been paid to inverse logistics. In this paper, a mixed integer stochastic location-inventory model has been proposed for the integrated design of the network of a multi-period multi-product closed loop supply chain considering multiple capacity levels for facilities. The market demand and correspondingly the return value are considered to be uncertain in order to make the model close to the real-life conditions. Since the capacitated facility location problem considered in this research is an NP-hard type problem, we have used two meta-heuristic algorithms including the genetic algorithm (GA) and the Bees algorithms (BA) for solving this problem. Some numerical problems are designed and solved to assess the performance of the model and solution heuristics. From the viewpoint of solution quality, the BA outperforms the GA (by an average of 11.6%) whilst from the viewpoint of solution time, the GA is five times faster than the BA on average. | ||
کلیدواژهها [English] | ||
Closed Loop Supply Chain, Network Design, Uncertainty, Genetic Algorithm, Bees Algorithm | ||
مراجع | ||
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