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
[1]
S. Chanas.
The use of parametric programming in fuzzy linear programming
,
1983
.
[2]
Richard Bellman,et al.
Decision-making in fuzzy environment
,
2012
.
[3]
C. Carlsson,et al.
A parametric approach to fuzzy linear programming
,
1986
.
[4]
Reay-Chen Wang,et al.
Aggregate production planning with multiple objectives in a fuzzy environment
,
2001,
Eur. J. Oper. Res..
[5]
Jiafu Tang,et al.
Fuzzy formulation for multi-product aggregate production planning
,
2000
.
[6]
O. S. Silva Filho,et al.
An aggregate production planning model with demand under uncertainty
,
1999
.
[7]
Madan M. Gupta,et al.
Fuzzy mathematical models in engineering and management science
,
1988
.
[8]
Suhua Hsieh,et al.
Demand and cost forecast error sensitivity analyses in aggregate production planning by possibilistic linear programming models
,
2000,
J. Intell. Manuf..