Analysis of Performance of Fuzzy Logic-Based Production Scheduling by Simulation

Alejandra Duenas, Dobrila Petrovic, Sanja Petrovic

    Research output: Contribution to journalArticle

    4 Citations (Scopus)


    in this paper, a new fuzzy logic-based approach to production scheduling in the presence of uncertain disruptions is presented. The approach is applied to a real-life problem of a pottery company where the uncertain disruption considered is glaze shortage. This disruption is defined by two parameters that are specified imprecisely: number of glaze shortage occurrences and glaze delivery time. They are modelled and combined using standard fuzzy sets and level 2 fuzzy sets, respectively. A predictive schedule is generated in such a way as to absorb the impact of the fuzzy glaze shortage disruption. The schedule performance measure used is makespan. Two measures of predictability are defined: the average deviation and the standard deviation of the completion time of the last job produced on each machine. In order to analyse the performance of the predictive schedule, a new simulation tool FPSSIM is developed and implemented. Various tests carried out show that the predictive schedules have good performance in the presence of uncertain disruptions.
    Original languageEnglish
    Pages (from-to)234-243
    JournalLecture Notes in Computer Science
    Issue number2005
    Publication statusPublished - 2005

    Bibliographical note

    This paper is not available on the repository. This paper was given at the 4th Mexican International Conference on Artificial Intelligence, Monterrey, Mexico, November 14-18, 2005


    • Artificial Intelligence (incl. Robotics)
    • Computation by Abstract Devices
    • Mathematical Logic and Formal Languages
    • Image Processing and Computer Vision


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