Multiproduct aggregate production planning with fuzzy demands and fuzzy capacities

Given the uncertain market demands and capacities in production environment, this paper discusses some practical approaches to modeling multiproduct aggregate production planning problems with fuzzy demands, fuzzy capacities, and financial constraints. By formulating the fuzzy demand, fuzzy equation, and fuzzy capacities, a fuzzy production-inventory balance equation for single period and a dynamic balance equation are formulated as fuzzy/soft equations and they represent the possibility levels of meeting the market demands. Using this formulation and interpretation, a fuzzy multiproduct aggregate production planning model is developed, and its solutions using parametric programming, best balance and interactive techniques are introduced to cater to different scenarios under various decision making preferences. Using the proposed models and techniques, first, the decision maker can select a preferred production plan with a common satisfaction level or different combinations of preferred possibility level and satisfaction levels, according to the market demands and available production capacities, and second, the obtained structure of the optimal solution can help decision maker in aggregate production planning. The decision maker can also make a preferred and reasonable production plan corresponding to one’s most concerned criteria. Hence, decision makers not only can come up with a reasonable aggregate production plan with minimum efforts, but also have more choices of making a preferred aggregate plan based on his most concerned criteria. These models can effectively enhance the capability of an aggregate plan to give feasible family disaggregation plans under different scenarios with fuzzy demands and capacities. Simulation and the results of analysis on the proposed techniques are also given in detail in this paper.

[1]  Gabriel R. Bitran,et al.  Deterministic Approximations to Stochastic Production Problems , 1984, Oper. Res..

[2]  Jaroslav Ramík,et al.  Fuzzy mathematical programming based on some new inequality relations , 1996, Fuzzy Sets Syst..

[3]  Umit Akinc,et al.  A New Approach to Aggregate Production Planning , 1986 .

[4]  Shu-Cherng Fang,et al.  A genetics-based approach for aggregated production planning in a fuzzy environment , 1997, IEEE Trans. Syst. Man Cybern. Part A.

[5]  Linet Özdamar,et al.  A hierarchical decision support system for production planning (with case study) , 1998 .

[6]  Jinxing Xie,et al.  An intelligent hybrid system for customer requirements analysis and product attribute targets determination , 1998 .

[7]  H. Tanaka,et al.  Fuzzy solution in fuzzy linear programming problems , 1984, IEEE Transactions on Systems, Man, and Cybernetics.

[8]  W. H. Hausman,et al.  A Note on the Bergstrom-Smith Multi-Item Production Planning Model , 1971 .

[9]  Jiafu Tang,et al.  A nonsymmetric model for fuzzy nonlinear programming problems with penalty coefficients , 1997, Comput. Oper. Res..

[10]  Richard Y. K. Fung,et al.  Product design resources optimization using a non-linear fuzzy quality function deployment model , 2002 .

[11]  Hans-Jürgen Zimmermann,et al.  Fuzzy mathematical programming , 1983, Comput. Oper. Res..

[12]  C. C. Holt,et al.  Planning Production, Inventories, and Work Force. , 1962 .

[13]  Roger G. Schroeder,et al.  Operations Management: Decision Making in the Operations Function , 1981 .

[14]  Richard Y. K. Fung,et al.  Model and Method Based on Ga for Nonlinear Programming Problems with Fuzzy Objective and Resources , 1998, Int. J. Syst. Sci..