A Genetic Algorithm for Solving a Special Class of Nonlinear Bilevel Programming Problems
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Solving Bilevel Multi-Objective Optimization Problems Using Evolutionary Algorithms
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
Application of particle swarm optimization algorithm for solving bi-level linear programming problem
Computers & Mathematics with Applications
Evolutionary computing in manufacturing industry: an overview of recent applications
Applied Soft Computing
Constructing test problems for bilevel evolutionary multi-objective optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Bilevel multi-objective optimization problem solving using progressively interactive EMO
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
INFORMS Journal on Computing
A hybrid genetic algorithm for solving a class of nonlinear bilevel programming problems
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
The r-interdiction median problem with probabilistic protection and its solution algorithm
Computers and Operations Research
Estimation of distribution algorithm for a class of nonlinear bilevel programming problems
Information Sciences: an International Journal
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In most real-life problems such as rolling system design decision-making can be hierarchical and the search space is unknown. Bilevel optimisation problem (BLP) is an operation research technique for solving real life hierarchical decision-making problems. There are a number of different algorithms developed based on classical optimisation methods to solve different classes of the BLP problems where the search space is known. There also exist a number of problems in the BLP which current algorithms are not sufficiently robust to solve. In this paper, Bi-level Genetic Algorithm (BiGA) is a new proposed to solve different classes of the BLP problems within a single framework. BiGA is an elitist optimisation algorithm developed to encourage limited asymmetric cooperation between the two players. The performance of the algorithm is illustrated using test functions. The results suggest that BiGA algorithm is robust to solve different classes of the BLP problems and demonstrates potential for real life problems.