ارائه مدل تصادفی مکان‌یابی- مسیریابی – موجودی فسادپذیر با در نظرگرفتن کمبود و زمان حمل

نوع مقاله : پژوهشی اصیل

نویسندگان
1 دانشجوی دکتری، گروه مدیریت صنعتی، دانشکده مدیریت واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران.
2 دانشیار، گروه مدیریت صنعتی، دانشکده مدیریت واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران.
3 استاد، گروه مهندسی صنایع، دانشکده مهندسی صنایع دانشگاه علم و صنعت ایران، تهران، ایران.
4 استاد، گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.
چکیده
با آشکارترشدن اهمیت مدیریت زنجیره تأمین نزد صاحبان صنعت، نقش هماهنگی و یکپارچگی مؤلفه‌های مختلف زنجیره تأمین در ایجاد مزیت رقابتی، پررنگ‌تر شده است. این مقاله یک مدل ریاضی جامع برای مسئله مکان‌یابی- مسیریابی- موجودی محصولات فاسد‌شدنی را با درنظرگرفتن کمبود، زمان حمل و ملاحظههای زیست‌محیطی در شرایط عدم‌قطعیت ارائه می‌دهد. بهاینمنظور، یک روش حل دقیق از راه فرمولهکردن مسئله به‌صورت برنامه‌ریزی غیرخطی عدد ‌صحیح مختلط با استفاده از رویکرد تصادفی مبتنی بر سناریو ارائه شده است که هم‌زمان مجموع هزینه‌های سیستم (هزینه مکان‌یابی مراکز با سطح ظرفیت معین، هزینه عملیاتی مراکز، هزینه‌های حملونقل و نگهداری موجودی و یا کمبود مرکز ترکیبی تولید/ بازرسی)، مجموع حداکثر زمان در زنجیره و انتشار آلاینده‌ها در کل شبکه را کمینه می‌کند. به‌دلیل NP-hardبودن مسئله، برای حل آن رویکردی از الگوریتم
ژنتیک پیشنهاد شده است. به‌منظور اعتبارسنجی، نتایج الگوریتم پیشنهادی در مثال‌های اندازه کوچک با نتایج حل روش دقیق مقایسه شده‌اند. نتایج نشان‌دهنده‌ توانایی الگوریتم پیشنهادی در رسیدن به جوابی با درصد اختلاف قابل‌قبول در زمانی بسیار کمتر نسبت به‌روش حل دقیق می‌باشد. همچنین نتایج حاصل از عملکرد الگوریتم براساس شاخص‌های استاندارد بررسی شده است. نتایج محاسباتی، کارایی مدل ارائهشده و روش حل پیشنهادی را نشان می‌دهد.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Presenting a stochastic location-inventory-routing model for perishable products with shortage and shipping time

نویسندگان English

sima hajian 1
Mohammad Ali Afshar Kazemi 2
seyed mohammad seyed hosseini 3
Abbas Toloie eshlaghi 4
1 Ph.D. Student, Department of Industrial Management, Faculty of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
2 Associate Prof., Faculty of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
3 Professor, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
4 Professor, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
چکیده English

As the importance of supply chain management becomes more evident to the industry owners, the role of cooperation and integration of supply chain different components has become more vivid in creating competitive advantage. This paper proposes a comprehensive mathematical model for location-inventory-routing problem of perishable products given shortage, shipping time, and environmental considerations under uncertainty. To this purpose, an accurate solution was proposed by formulating the problem as non-linear programming of mixed integer using scenario-based stochastic approach. This approach simultaneously minimizes the sum of system costs (the cost of locating centers with certain level of capacity, operational cost of centers, transportation costs, maintaining inventory, and/or shortage of combined center of production/inspection), the sum of maximum time in the chain and emission of pollutants in the whole network. As the problem is NP-hard, a genetic algorithm approach has been proposed to solve the model. For validation, the results of the proposed algorithm in the small size examples were compared to the results of precise solution method. The obtained results revealed the capability of the proposed algorithm in reaching a solution with acceptable percentage difference and in a very shorter time compared to precise solution method. Additionally, the results from algorithm performance were investigated based on standard indicators. The computational results show the efficiency of the proposed model and solution method.

کلیدواژه‌ها English

Location-Inventory-Routing
Multi-Objective Stochastic Programming
Perishable
genetic algorithm
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