Scopus İndeksli Yayınlar Koleksiyonu

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Browsing Scopus İndeksli Yayınlar Koleksiyonu by Journal "11th Annual International Conference on Industrial Engineering and Operations Management IEOM 2021"

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    Aisle-to-aisle design for SBS/RS under smart deadlock control policies
    (IEOM Society, 2021) Ecem Eroğlu Turhanlar; Banu Yetkin Yetkin Ekren; Tone Lerher; Lerher, Tone; Turhanlar, Ecem Eroglu; Ekren, Banu Yetkin
    Recent increase in e-commerce warehouse operations have become one of the most significant issues. Recent customer profile requests fast delivery time with flexible options in purchasing. Automated warehousing technologies are widely utilized in warehouses to provide fast solutions for those demand profiles. Shuttle-based storage and retrieval system (SBS/RS) is an automated warehousing technology assuring fast transaction process in warehouses. In this work we study a special design for SBS/RS where automated vehicles (i.e. shuttles) are more flexible in their travel pattern so that the system would not require a dedicated shuttle in each tier resulting with decreased number of shuttles compared to a dedicated one (i.e. each zone with a single shuttle) in the system. We compare these two system designs flexible and dedicated ones by using an agent-based simulation modelling approach. The proposed flexible design is developed on deadlock and collision prevention algorithms evaluating real time information. The performance of the system is compared by their average flow time per transaction maximum flow time of a transaction throughput rate and utilization of shuttles etc. The results show that by integrating smart collision and deadlock prevention algorithms the proposed flexible aisle-to-aisle SBS/RS works better than the dedicated system design. © 2021 Elsevier B.V. All rights reserved.
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    Smart transaction picking in tier-to-tier SBS/RS by deep Q-learning
    (IEOM Society, 2021) Bartu Arslan; Banu Yetkin Yetkin Ekren; Arslan, Bartu; Ekren, Banu Y.
    By the rapid growth of e-commerce the intralogistics sector is facing new challenges. Intralogistics sector requires more flexible scalable processes with maximum reliability and availability. They are complicated and interconnected systems whose all components are required to be perfectly coordinated with each other for optimal functionality. In this work we study an intralogistics technology shuttle-based storage and retrieval system (SBS/RS) where shuttles are tier-to-tier. In this novel system design in an effort to increase shuttle utilization as well as decrease initial investment cost shuttles are designed in a more flexible travel manner so that they can change their tiers within an aisle by using a separate lifting mechanism. Due to the complexity of such system design as well as aiming to obtain fast transaction process time by the decreased number of shuttles in the system we implement a Deep Q-Learning (DQL) approach to let shuttles select the best transaction to process based on its targets. We compare the performance of the DQL by the average cycle time per transaction performance metric with the other well-known selection rules First-in-First-Out (FIFO) and Shortest Process Time (SPT). Results show that Deep Q-Learning approach produces better results than those FIFO and SPT. © 2021 Elsevier B.V. All rights reserved.