ارایه الگوریتم رقابت استعماری چندهدفه جهت بهینه ‏سازی مسئله ی برنامه‏ ریزی تولید ادغامی پایا

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشیار، گروه مهندسی صنایع، دانشکده مهندسی، دانشگاه بوعلی سینا، همدان.

2 دانشجوی دکتری، گروه مهندسی صنایع، دانشکده مهندسی، دانشگاه بوعلی سینا، همدان.

چکیده

در این مقاله، مدلی دوهدفه برای یک مسئله ی برنامه‏ ریزی تولید ادغامی چندمحصولیِ چند دوره‏ای در زنجیرۀ تأمینی شامل تعدادی تأمین‏ کننده، تولیدکننده و نقطۀ تقاضا ارائه شده است که از یک طرف به دنبال کمینه ‏سازی هزینۀ کل زنجیرۀ تأمین شامل هزینه ‏های نگهداری موجودی، هزینه‏ های تولید، هزینه ‏های نیروی انسانی، هزینه‏ های جذب و از دست دادن نیروی انسانی می ‏باشد و از طرف دیگر و به صورت همزمان با استفاده از بیشینه ‏سازی حداقل قابلیت اطمینان کارخانه ‏های تولیدی با در نظر گرفتن زمان‏ های تحویل‏ احتمالی، به دنبال بهبود عملکرد سیستم و برنامۀ تولید پایاتری است. در نهایت با توجه به اینکه مسألۀ مذکور NP-hard می ‏باشد، برای حل مدل پیشنهادی از یک الگوریتم رقابت استعماری چندهدفه مبتنی بر پارتو استفاده شده و به منظور بررسی عملکرد الگوریتم مذکور، الگوریتم ژنتیک مرتب‏سازی نامغلوب (NSGA-II) نیز بکار رفته است. نتایج حاصل از مسائل آزمایشی تولید شده، توان الگوریتم پیشنهادی را در یافتن جواب‏های پارتو نشان می‏ دهد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Proposing a Multi-objective Imperialist Competitive Algorithm to Optimize Reliable Aggregate Production Planning Problem

نویسندگان [English]

  • Amir Saman Kheirkhah 1
  • Arash Nobari 2
  • Vahid Hajipour 2
1 Associate Professor
2 PhD candidate/ Bu-Ali Sina University
چکیده [English]

In this paper, a bi-objective model is developed to deal with an aggregate production planning problem in a multi product, multi period supply chain including multiple suppliers, factories and demand points. This bi-objective model aims to minimize the total cost of supply chain including inventory costs, manufacturing costs, work force costs, hiring, and firing costs, and maximize the minimum of producers' reliability by considering probabilistic lead times, to improve performance of the system and achieve a more reliable production plan. Since the proposed bi-objective model is NP-hard, a Pareto-based multi-objective imperialist competitive algorithm (MOICA) is used. To evaluate the performance of presented algorithm, non-dominated sorting genetic algorithm (NSGA-II) is applied, too. The results show the capability and efficiency of proposed algorithm in finding Pareto solutions.    

کلیدواژه‌ها [English]

  • Aggregate production planning
  • Supply chain management
  • Multi-objective optimization
  • multi-objective imperialist competitive algorithm (MOICA)

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