Details

Autor(en) / Beteiligte

• Wang, Guangmin
• Ma, Linmao
• Chen, Jiawei

Titel

A bilevel improved fruit fly optimization algorithm for the nonlinear bilevel programming problem

Ist Teil von

• Knowledge-based systems, 2017-12, Vol.138, p.113-123

Ort / Verlag

Amsterdam: Elsevier B.V

Erscheinungsjahr

2017

Quelle

Access via ScienceDirect (Elsevier)

Beschreibungen/Notizen

• •We propose a BIFOA to solve the nonlinear bilevel programming problems (NBLPP).•NBLPP is treated as two common nonlinear programming problems to solve in BIFOA.•BIFOA is applied to solve NBLPP including high-dimensional problems.•The numerical experiments shows the efficiency and outperformance of BIFOA. 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.