Title :
Solving fuzzy problems in operations research: inventory control
Author :
Buckley, James J. ; Feuring, Thomas ; Hayashi, Yoichi
Author_Institution :
Dept. of Math., Alabama Univ., Birmingham, AL, USA
Abstract :
We are interested in generating good approximate solutions to single item, N-period, fuzzy inventory control problems. It is a fuzzy inventory control problem since some of the parameters (ordering cost, holding cost, penalty cost) can be fuzzy numbers. We consider two cases: (1) demand is known each period, and (2) demand is unknown, and fuzzy each period. We employ an evolutionary algorithm to search out good approximate solutions
Keywords :
decision theory; evolutionary computation; fuzzy set theory; minimisation; search problems; stock control; evolutionary algorithm; fuzzy problems; good approximate solutions; holding cost; operations research; ordering cost; penalty cost; single item N-period fuzzy inventory control problems; Computer science; Cost function; Equations; Evolutionary computation; Fuzzy control; Inventory control; Mathematics; Operations research;
Conference_Titel :
Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-5877-5
DOI :
10.1109/FUZZY.2000.838685
