Publicación: A STOCHASTIC HIERARCHICAL APPROACH FOR A PRODUCTION PLANNING SYSTEM UNDER UNCERTAIN DEMANDS
Fecha
2017
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DATA ANALYTICS APPLICATIONS IN LATIN AMERICA AND EMERGING ECONOMIES
Resumen
HIERARCHICAL PRODUCTION PLANNING IS A WIDELY UTILIZED METHODOLOGY FOR REAL WORLD PRODUCTION PLANNING SYSTEMS, WITH THE AIM TO ESTABLISH ALTERNATIVE DECISION-MAKING LEVELS OF THESE PLANNING ISSUES. FOR TACTICAL PURPOSES, THE METHODOLOGY CONSIDERING ONE OR TWO DISAGGREGATION LEVELS, IN ORDER TO MEET THE FINAL DEMAND. FREQUENTLY, THE HIERARCHICAL APPROACH UTILIZES DIFFERENT DETERMINISTIC OPTIMIZATION MODELS THAT IMPOSE APPROPRIATE CONSTRAINTS TO KEEP COHERENCE OF THE PLAN ON THE PRODUCTION SYSTEM. HOWEVER, IN MANY SITUATIONS, A DETERMINISTIC MODEL ISN?T APPROPRIATE FOR CAPTURING UNCERTAIN DEMAND BEHAVIOR THAT IS PRESENT IN SOME REAL-WORLD APPLICATIONS. ONE UNCERTAINTY TO BE CONSIDERED IS THE INVOLVEMENT OF OPTIMIZATION MODELS IN WHICH THIS PARAMETER IS REPRESENTED BY A RANDOM VARIABLE OR A SET OF SCENARIOS. FOR THAT PURPOSE, IN THE PROPOSED CHAPTER, WE INTRODUCE A HIERARCHICAL APPROACH USING DIFFERENT STOCHASTIC OPTIMIZATION MODELS, IN ORDER TO DETERMINE OPTIMAL ALLOCATION OF RESOURCES AT THE TACTICAL LEVEL, AS WELL AS IN REFERENCE TO THE MOST IMMEDIATE PLANNING HORIZON, IN ORDER TO MEET UNCERTAIN DEMANDS. WE ALSO PRESENT A CASE STUDY APPLYING THE PROPOSED METHODOLOGY TO AN INDUSTRIAL COMPANY THAT PRODUCES DIFFERENT HOUSE HOLD ELECTRICAL APPLIANCES, ELUCIDATING THE RELEVANCY OF THE ADOPTED METHODOLOGY.
