الگوریتم ترکیبی داده‌کاوی و مدل‌سازی زنجیره تأمین مبتنی بر داده برای تخصیص کالا به انبارها و خدمت‌دهی انبار به مشتریان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، دانشگاه شهید بهشتی.

2 دانشجوی کارشناسی ارشد، دانشگاه شهید بهشتی.

چکیده

در این پژوهش، موضوع تخصیص کالا در شرایطی که تنوع کالا و تعداد مشتریان زیاد است، مورد بررسی قرار می‌گیرد. گسترش سطح دسترسی به اینترنت و افزایش میل به خرید آنلاین، تعداد مشتریان را افزایش داده است. در شرایطی که تنوع کالا و تعداد مشتریان زیاد است، حل مسائلی مانند تحویل به موقع کالا یا خدمات، انتخاب و تعیین سفارش‌ها در انبارهای غیر متمرکز و موضوع تخصیص انبار به مشتریان دشوار است. برای حل این چالش‌ها، استفاده از مدل‌سازی ریاضی با روش‌های حل فراابتکاری پیشنهاد شده است. اما به دلیل تعداد زیاد حالت‌های تخصیص، حل مدل‌های ریاضی بسیار پیچیده و زمانبر است. با بهبود قدرت محاسباتی و فضای ذخیره سازی، روش‌های مبتنی بر داده برای حل این چالش‌ها توسط محققان مورد مطالعه قرار گرفته است. در این تحقیق، یک راه‌حل ترکیبی مبتنی بر داده که از داده‌کاوی و مدل سازی‌ریاضی استفاده می‌کند، تا تنوع کالاها و تعداد مشتریان را مدیریت کند، پیشنهاد شده است که در زمان کمتری مدل‌های ریاضی تخصیص را با دقت بالا، حل می‌کند. این روش روی داده‌های «دیجی کالا» پیاده سازی شده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

A Hybrid Data-Mining Algorithm and Data-Driven Supply Chain Modeling for Allocation Goods to Warehouses and Warehouse Service to Customers

نویسندگان [English]

  • Sadra Ahmadi 1
  • Reza Yousefpour 2
1 Assistant Professor, Shahid Beheshti University.
2 Master Student, Shahid Beheshti University.
چکیده [English]

In this research, the issue of product allocation in a situation that there are a large number customers and goods are various, is investigated. Expanding the level of Internet access and increasing the desire of online shopping, raise the number of customers. In a situation where there is a great variety of goods and a large number of customers, it is difficult to solve issues such as on-time delivery of goods or services, selection and ordering in decentralized warehouses, and the issue of warehouse allocation to customers. To solve these challenges, the use of mathematical modeling with meta-heuristic solution methods has been proposed so far, but due to the large number of allocation modes, solving mathematical models is very complex and it takes time. With the improvement of computing power and storage space, data-driven methods have been studied by researchers to solve these challenges. In this study, a hybrid data-driven solution that uses data mining and mathematical modeling to manage the variety of goods and the number of customers has been proposed, that manages the variety of goods and the number of customers, and can solve mathematical models in less time. This method has been implemented on the data of "DigiKala".

کلیدواژه‌ها [English]

  • Supply Chain
  • Warehouse Location
  • Data Mining
  • Warehouse Allocation
  • Clustering

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