TY - CHAP
T1 - Credibilistic Programming
AU - Li, Xiang
N1 - Publisher Copyright:
© 2013, Springer-Verlag Berlin Heidelberg.
PY - 2013
Y1 - 2013
N2 - The decision analysis with fuzzy objective or fuzzy constraints is natural in some real-world applications, and sometimes such analysis seems to be inevitable. Credibilistic programming is a type of mathematical programming for handling the fuzzy decision problems. In the past years, researchers have proposed various efficient modeling approaches including expected value model, chance-constrained programming model, entropy optimization model, cross-entropy minimization model, and regret minimization model. This chapter provides a general description on credibilistic programming. In addition, a brief introduction on genetic algorithm will also be given.
AB - The decision analysis with fuzzy objective or fuzzy constraints is natural in some real-world applications, and sometimes such analysis seems to be inevitable. Credibilistic programming is a type of mathematical programming for handling the fuzzy decision problems. In the past years, researchers have proposed various efficient modeling approaches including expected value model, chance-constrained programming model, entropy optimization model, cross-entropy minimization model, and regret minimization model. This chapter provides a general description on credibilistic programming. In addition, a brief introduction on genetic algorithm will also be given.
KW - Credibilistic Mapping
KW - Credibilistic Programming
KW - Fuzzy Objective
KW - Genetic Algorithm
KW - Roulette Wheel
UR - https://www.scopus.com/pages/publications/85125870699
U2 - 10.1007/978-3-642-36376-4_2
DO - 10.1007/978-3-642-36376-4_2
M3 - Chapter
AN - SCOPUS:85125870699
T3 - Uncertainty and Operations Research
SP - 31
EP - 44
BT - Uncertainty and Operations Research
PB - Springer Nature
ER -