به‎کارگیری الگوریتم ژنتیک برای برنامه‌ریزی تأمین، تولید و توزیع یکپارچۀ سیستم‌های مونتاژ

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشجوی دکتری مدیریت تولید و عملیات، دانشکدۀ مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران

2 استاد گروه مدیریت صنعتی، دانشکدۀ مدیریت دانشگاه تهران، تهران، ایران

چکیده

با وجود این حقیقت که در بیشتر پژوهش­ها، تنها بخشی از زنجیرۀ تأمین مطالعه شده است؛ در این مطالعه تلاش می‎شود به بررسی برنامه‎ریزی‎ای برای تأمین، تولید و توزیع یکپارچه پرداخته ‎شود. بنابراین پژوهش پیش رو، نوعی مدل ریاضی را به‎منظور مدیریت موجودی برای سطوح زنجیرۀ تأمین توسعه داده است؛ به‎گونه­ای که سیاست سفارش­دهی مناسب را برای سطوح تأمین، تولید و توزیع زنجیره مشخص کند و همچنین هزینه­های مرتبط با آن را به کمترین حد برساند. مسئلۀ این مطالعه به‎عنوان برنامه­ریزی عدد صحیح محض فرموله می‎شود و برای حل آن روش الگوریتم ابتکاری ژنتیک به‎کار می‎رود؛ سپس مدل ساخته‎شده در نمونۀ واقعی استفاده می‎شود. نتایج تجربی به‎دست‎آمده نشان می­دهد به‎کارگیری این مدل می­تواند هزینه­های موجودی شرکت نمونه را تا حد 4694/8 درصد کاهش دهد

کلیدواژه‌ها

عنوان مقاله [English]

Applying Genetic Algorithm for An integrated Supply and Production/Distribution Planning in assembly systems

نویسندگان [English]

  • Mohammad Sabet Motlagh 1
  • Ali Mohaghar 2
1 PhD Candidate, Faculty of Management and Accounting, Allameh Tabatabaee University, Tehran, Iran
2 Prof. Industrial Management, Tehran University, Tehran, Iran
چکیده [English]

Abstract: An efficient supply chain system operates under a strategy to minimize costs by integrating the different functions inside the system and by meeting customer demands in time. In this paper, an integrated supply-production and distribution planning (SPDP) is considered despite the fact that in most of the Papers, Part of the supply chain has been studied, not all parts. Therefore, we develop a mathematical model that calculate the optimal inventory lot sizing for each supplier and minimize the total cost associated in the process of procuring raw material, transferring and holding raw materials, manufacturing and, finally, delivering the finished product. The problem is formulated as a pure integer programming and heuristic genetic algorithm (GA) method applied to solve it. Then we test the proposed model in a case study conducted in Iran. Experimental results show that such a model can reduce the costs of the case study by 8/4694%.

کلیدواژه‌ها [English]

  • Genetic Algorithm
  • Inventory management
  • Mathematical modeling
  • pure integer programming
  • Supply Chain Management

مراجع

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مدیریت صنعتی
دوره 8، شماره 2
مرداد 1395
صفحه 163-190

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