Unbalanced Bidding Problem with Fuzzy Random Variables

Dongran Zang, Liang Lin, Xingzi Liu

Abstract


Unbalanced bidding problem with mixed uncertainty of fuzziness and randomness is considered in this paper, where the bidding engineering quantities of each activity are assumed to be fuzzy random variables. Two types of fuzzy random models as expected value maximization model and maximax chance-constrained model are built to satisfy different optimization requirements. Then a hybrid intelligent algorithm integrating fuzzy random simulations, neural network and genetic algorithm is designed to solve these models. Finally, a numerical experiment is given to illustrate its effectiveness of the algorithm. The results show that the algorithm is feasible and effective.


Full Text: PDF

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

International Business Research  ISSN 1913-9004 (Print), ISSN 1913-9012 (Online)

Copyright © Canadian Center of Science and Education

To make sure that you can receive messages from us, please add the 'ccsenet.org' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.