Title :
Solving combinatorial optimization problems with fuzzy weights
Author :
Kasperski, Adam ; Ziefinski, P.
Author_Institution :
Inst. of Ind. Eng. & Manage., Wroclaw Univ. of Technol., Wroclaw
Abstract :
In this paper a combinatorial optimization problem with fuzzy weights is discussed. In order to choose a solution the concept of a necessary soft optimality is adopted. It is shown that the fuzzy problem can be reduced to solving a family of interval problems with the maximal regret criterion. Two general methods of solving the interval problems are presented. The first one is based on a branch and bound technique and the second method is based on a mixed integer programming formulation. Both techniques are general and can be applied if the underlying interval problem is NP-hard.
Keywords :
combinatorial mathematics; computational complexity; fuzzy set theory; integer programming; tree searching; NP-hard; branch-and-bound technique; combinatorial optimization; fuzzy weights; interval problem; maximal regret criterion; mixed integer programming; soft optimality; Engineering management; Fuzzy set theory; Industrial engineering; Linear programming; Mathematics; Minimax techniques; Possibility theory; Shortest path problem; Technology management; Uncertainty;
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2008.4630384