روش کارای یادگیری ترجیحات مبتنی بر مدل ELECTRE TRI به‎منظور طبقه‌بندی چندمعیارۀ موجودی

نوع مقاله: مقاله علمی پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد گروه مدیریت صنعتی، دانشگاه آزاد اسلامی، واحد الکترونیکی، تهران، ایران

2 استادیار گروه مدیریت صنعتی، دانشگاه آزاد اسلامی، واحد الکترونیکی، تهران، ایران

چکیده

آنالیز چندمعیارۀ ABC روش شناخته‎شده‎ای برای طبقه‌بندی موجودی‌هاست که اغلب رویکرد جبرانی را برای تجمیع معیارها لحاظ می‎کند، یعنی ضعف موجودی در یک معیار با عملکرد خوب آن در معیارهای دیگر جبران می‎شود. تا جایی که می‎دانیم رویکرد غیرجبرانی این مسئله به‎طور کافی مطالعه ‌نشده ‌است. مدل ELECTRE TRI از مدل‎های مبتنی بر روابط ‌برتری ‌است که این رویکرد را در محاسبات لحاظ‌ می‌کند، ولی با توجه به‌ پیچیدگی و هزینه‌بربودن، این مدل در تعیین مقادیر ترجیحات ‌تصمیم‌گیرندگان (پارامترها)، از اقبال ‌خوبی برخوردار ‌نبوده است. بدین منظور در ‌این ‌مقاله روشی ارائه ‌می‎شود که با ‌استفاده از الگوریتم‌ بهینه‌سازی‌ تراکم‌ ذرات (PSO)، مقادیر تمام پارامترها را از داده‌های آموزشی شامل تصمیمات قبلی تصمیم‎گیرندگان یاد‌ می‎گیرد و در طبقه‌بندی موجودی‌های جدید به‎کار می‎برد. روش‌ پیشنهادی برخلاف ‌مدل‌های استاندارد داده‌کاوی که طبقه‌بندی را به‌صورت اسمی انجام‌ می‌دهند، متناسب با روش ABC اقلام موجودی را به‌صورت ‌رتبه‌ای طبقه‎بندی می‎کند. نتایج ‌به‎دست‌آمده از آنالیز تجربی ‌روش‌ پیشنهادی روی دیتاست‌های‌ موجودی، کارایی و قابلیت رقابت آن را در مقایسه ‌با‌ سایر مدل‌های‌ طبقه‌بندی نشان‌ می‌دهد.

کلیدواژه‌ها


عنوان مقاله [English]

An efficient preference learning method based on ELECTRE TRI model for multi-criteria inventory classification

نویسندگان [English]

  • Masoud ZarrinSadaf 1
  • Amir Daneshvar 2
1 MSc. Student in Industrial Management, Islamic Azad University, Tehran, Iran
2 Assistant Prof., Islamic Azad University E-Campus, Tehran, Iran
چکیده [English]

The multi-criteria ABC analysis is a well known inventory management method for classifying inventory. In the most ABC classification applications, it has been considered fully compensatory approaches, i.e. items have been privilege badly in one or more criteria could be placed in good classes, so it is necessary non-compensatory approach to be noticed. ELECTRE TRI is an outranking relations based model that consider non-compensatory approach, although suffers from the complexity and cost of determining the large number of decision-makers preferences (parameters). In this paper we propose a new method which learns all the decision-makers' preferences from assignment example at the same time using the Particle Swarm Optimization(PSO) algorithm, and will be applied in ABC classification. Against the data mining standard techniques that classify items in nominal way, this model has the ability to categorize items into ordinal classes. The evaluation of proposed method on the illustrated inventory datasets shows high quality and competitive results compared with several standard classification models.

کلیدواژه‌ها [English]

  • ABC Analysis
  • ELECTRE TRI
  • Multi-criteria inventory classification
  • Particle Swarm Optimization (PSO)
  • Swarm Algorithms
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