An Improved Fuzzy Knowledge-Based Model For Long Stay Container Yards

Ammar Al Bazi, Vasile Palade, Rami Al-Hadeethi, Ali Abbas

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    This paper considers the problem of allocating newly arrived containers to stacks of existing containers in a yard when the departure date/time for containers is unknown. Many factors and constraints need to be considered when modelling this storage allocation problem. These constraints include the size, type and weight of the containers. The factors are the number of containers in a stack and the duration of stay of the topmost container in the stack. This paper aims to develop an improved Fuzzy Knowledge-Based ‘FKB’ model for best allocation
    practice of long-stay containers in a yard. In this model, the duration of stay factor does not need to be considered in the allocation decision if the duration of stay for the topmost containers in a stack is similar; hence, a new ‘ON/OFF’ strategy is proposed within the Fuzzy Knowledge-Based model to activate/deactivate this factor in the stacking algorithm whenever is required. Discrete Event Simulation and Fuzzy Knowledge-Based techniques are used to develop the proposed model. The model’s behaviour is tested using three real-life scenarios, including allocating containers in busy, moderately busy and quiet yards. The total number of re-handlings, the number of re-handlings per stack, and the number of re-handlings for containers were considered KPIs in each scenario.
    Original languageEnglish
    Number of pages9
    JournalAdvances In Industrial Engineering And Management
    Issue number1
    Publication statusPublished - 10 Jun 2021

    Bibliographical note

    This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


    • Fuzzy Knowledge-Based Model
    • Fuzzy Rules, Long Stay Containers
    • Duration of Stay Factor
    • ‘ON/OFF’ Strategy
    • Container Yard Operations
    • Unknown Departure Time


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