Title :
Optimization with fuzzy linear programming and fuzzy knowledge base
Author :
Ren, Jie ; Sheridan, Thomas B.
Author_Institution :
Human-Machine Syst. Lab., MIT, Cambridge, MA, USA
Abstract :
Due to the complexity of modern systems, a decision process is most often dependent at least in part on qualitative reasoning, especially in the case where human involvement is important. The paper proposes an optimization methodology-fuzzy linear programming coordinated with a fuzzy linguistic knowledge base-to handle quantitative and qualitative information simultaneously. In this approach, fuzzy linear programming is used to model quantitatively the basic resource constraints and objective functions, while a linguistic knowledge base is used to model imprecise human expertise. Freight train dispatching, in which a physical rail network is very complex and human expertise of a yardmaster plays an important role in decision making, illustrates the application
Keywords :
common-sense reasoning; computational linguistics; fuzzy logic; fuzzy set theory; knowledge based systems; linear programming; basic resource constraints; decision making; decision process; freight train dispatching; fuzzy knowledge base; fuzzy linear programming; fuzzy linguistic knowledge base; human expertise; human involvement; imprecise human expertise modelling; linguistic knowledge base; objective functions; optimization methodology; physical rail network; qualitative reasoning; yardmaster; Decision making; Fuzzy systems; Humans; Laboratories; Linear programming; Man machine systems; Mathematical model; Mathematical programming; Optimization methods; Uncertainty;
Conference_Titel :
Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1896-X
DOI :
10.1109/FUZZY.1994.343565