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)

    Abstract

    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
    Volume3789
    Issue number2005
    DOIs
    Publication statusPublished - 2005

    Fingerprint

    Glazes
    Production/scheduling
    Fuzzy Logic
    Fuzzy logic
    Schedule
    Shortage
    Scheduling
    Fuzzy sets
    Fuzzy Sets
    Simulation
    Predictability
    Completion Time
    Simulation Tool
    Performance Measures
    Standard deviation
    Two Parameters
    Deviation
    Industry

    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

    Keywords

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

    Cite this

    Analysis of Performance of Fuzzy Logic-Based Production Scheduling by Simulation. / Duenas, Alejandra; Petrovic, Dobrila; Petrovic, Sanja.

    In: Lecture Notes in Computer Science, Vol. 3789, No. 2005, 2005, p. 234-243.

    Research output: Contribution to journalArticle

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