Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6862094 | Knowledge-Based Systems | 2017 | 11 Pages |
Abstract
This paper proposes a bilevel improved fruit fly optimization algorithm (BIFOA) to address the nonlinear bilevel programming problem (NBLPP). Considering the hierarchical nature of the problem, this algorithm is constructed by combining two sole improved fruit fly optimization algorithms. In the proposed algorithm, the lower level problem is treated as a common nonlinear programming problem rather than being transformed into the constraints of the upper level problem. Eventually, 10 test problems are selected involving low-dimensional and high-dimensional problems to evaluate the performance of BIFOA from the aspects of the accuracy and stability of the solutions. The results of extensive numerical experiments and comparisons reveal that the proposed algorithm outperforms the compared algorithms and is significantly better than the methods presented in the literature; the proposed algorithm is an effective and comparable algorithm for NBLPP.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Wang Guangmin, Ma Linmao, Chen Jiawei,