The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Genetic Algorithm for FGP Model of a Multiobjective Bilevel Programming Problem in Uncertain Environment
Abstract
This chapter describes a Genetic Algorithm (GA) based Fuzzy Goal Programming (FGP) model to solve a Multiobjective Bilevel Programming Problem (MOBLPP) with a set of chance constraints within a structure of decentralized decision problems. To formulate the model, the chance constraints are converted first to their crisp equivalents to employ FGP methodology. Then, the tolerance membership functions associated with fuzzily described goals of the objective functions are defined to measure the degree of satisfaction of Decision Makers (DMs) with achievement of objective function values and also to obtain the degree of optimality of vector of decision variables controlled by upper-level DM in the decision system. In decision-making process, a GA scheme is adopted to solve the problem and thereby to obtain a proper solution for balancing execution powers of DMs in uncertain environment. A numerical example is provided to illustrate the method.
Related Content
|
S. Karthigai Selvi, Sharmistha Dey, Siva Shankar Ramasamy, Krishan Veer Singh.
© 2025.
16 pages.
|
|
S. Sheeba Rani, M. Mohammed Yassen, Srivignesh Sadhasivam, Sharath Kumar Jaganathan.
© 2025.
22 pages.
|
|
U. Vignesh, K. Gokul Ram, Abdulkareem Sh. Mahdi Al-Obaidi.
© 2025.
22 pages.
|
|
Monica Bhutani, Monica Gupta, Ayushi Jain, Nishant Rajoriya, Gitika Singh.
© 2025.
24 pages.
|
|
U. Vignesh, Arpan Singh Parihar.
© 2025.
34 pages.
|
|
Sharmistha Dey, Krishan Veer Singh.
© 2025.
20 pages.
|
|
Kalpana Devi.
© 2025.
26 pages.
|
|
|