Affiliations: Industrial Systems Engineering, University of Regina,
Regina, Saskatchewan, S4S 0A2, Canada | Computer Science, University of Regina, Regina,
Saskatchewan, S4S 0A2, Canada | Industrial Systems Engineering, University of Regina,
Regina, Saskatchewan, S4S 0A2, Canada
Abstract: Uncertainties and imprecise information regarding customer demands,
production, inventory, and MRP are very common in performing aggregate
production-planning (APP) for the manufacturing in real world. This study
presents a fuzzy linear programming approach for managing the uncertainties and
imprecise information involved in industrial APP applications. Detailed
discussions are given to the establishment of the Fuzzy Linear Programming
approach with converting the fuzzy constraints of uncertain and imprecise items
into deterministic equivalents. A mathematical model is developed for APP
practice with the Fuzzy Linear Programming approach. For numerically performing
an aggregate production planning with the Fuzzy Linear Programming developed, a
computer simulation for an actual aggregate production-planning is presented.
It is demonstrated in the study, the employment of the Fuzzy Linear Programming
provides a great advantage in APP of manufacturing, if the parameters of the
stochastic factors involved in the production planning are neither definitely
reliable nor precise. The present study shows that the interrelated effects of
the customer service level and facility capacity on the effectiveness and
efficiency of aggregate production-planning is significant and should be taken
into account in performing an aggregate production-planning
Keywords: aggregate production-planning, fuzzy linear programming, manufacturing
