بکارگیری هوش مصنوعی در شرکت حمل و نقل چند وجهی مپنا در راستای یافتن بار بهینه ریلی

نوع مقاله : علمی - پژوهشی

نویسندگان

1 پژوهشگر پسادکتری، دانشکده اقتصاد و مدیریت، دانشگاه آزاد اسلامی واحد علوم و تحقیقات، تهران، ایران

2 استاد، دانشکده اقتصاد و مدیریت، دانشگاه آزاد اسلامی واحد علوم و تحقیقات، تهران، ایران

چکیده

گسترش روزافزون تقاضا در حوزه حمل و نقل ریلی باری و رقابتی بودن قیمت حمل کالا و کرایه حمل ریلی نسبت به سایر شقوق حمل و نقل در کشور یکی از مهمترین دلایل ضروری در توسعه و سرمایه گذاری هرچه بیشتر در این بخش از حمل و نقل است. معیارهای متفاوتی در حوزه حمل بار ریلی، چه از سوی صاحبان کالا و چه از سوی شرکتهای حمل و نقل ریلی و دارای مجوز صدور بارنامه ریلی، در سالهای اخیر مورد بحث و بررسی قرار گرفته است. هدف اصلی از این مقاله، بکارگیری هوش مصنوعی در شرکت حمل و نقل چند وجهی مپنا بعنوان یکی از شرکتهای مهم در عرصه حمل کالای ریلی، در راستای یافتن بار بهینه است. در این مقاله پیاده‌سازی شبکه های عصبی مصنوعی چند لایه و تشریح کدهای پیاده‌سازی ؛از طریق زبان برنامه‌نویسی پایتون، انجام شده وپس از ارزیابی و تنظیم پارامترهای مدل، وزن­های شبکه به وسیله کتابخانه pickle ذخیره سازی گشت که از این وزن­ها می­توان برای تخمین داده­های جدید استفاده کرد. پس از بررسی ۸۹۲۷۵ بارنامه موجود در حوزه شبکه ریلی کشور، اطلاعات بارنامه های ذکر شده به برنامه شبیه سازی شده وارد گردید که فرمول اصلی آن توسط خبرگان صنعت و کارشناسان راه آهن فرموله گردیده بود. نتایج، بارهای بهینه ریلی از میان بارنامه های صادر شده از حیث درآمد بیشتر و هزینه های کمتر، نشان می دهد.

کلیدواژه‌ها


عنوان مقاله [English]

Applying Artificial Intelligence in MAPNA Multimodal Transportation Company in Order to Find the Optimal Rail Load

نویسندگان [English]

  • hamidreza salmani mojaveri 1
  • abbas toloie Eshlaghi 2
1 Postdoctoral Researcher, Management and Economic School, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Professor, Management and Economic School, Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
چکیده [English]

The ever-increasing demand in the field of rail freight transportation and the competitiveness of the price of goods transportation and rail transportation fares compared to other transportation sectors in the country is one of the most important reasons for the development and investment as much as possible in this sector of transportation. Different criteria in the field of rail cargo transportation, both by the owners of the goods and by the rail transportation companies licensed to issue a rail bill of lading, have been discussed and investigated in recent years. The main purpose of this article is to apply the use of artificial intelligence in MAPNA multimodal transportation company as one of the important companies in the field of rail cargo transportation, in order to find the optimal load. In this article, the implementation of multi-layer artificial neural networks and the description of the implementation codes were done through the Python programming language and after evaluating and adjusting the model parameters, the weights of the network were stored by the pickle library that can be used to estimate new data. After checking 89275 bills of lading available in the railway network, the information of the mentioned bills of lading was entered into the simulated program, the main formula of which was formulated by industry experts and railway experts. The results of the optimal rail load from among the issued bills of lading show more income and lower costs.

کلیدواژه‌ها [English]

  • artificial intelligence
  • freight rail transport
  • optimal load
  • MAPNA multimodal transport company
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