Algorithms for solving the mixed integer two-level linear programming problem
Computers and Operations Research
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Fuzzy Sets and Systems - Special issue: Optimization and decision support systems
Bi-Level Optimisation Using Genetic Algorithm
ICAIS '02 Proceedings of the 2002 IEEE International Conference on Artificial Intelligence Systems (ICAIS'02)
Genetic Algorithms for Solving Linear Bilevel Programming
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
Practical Bilevel Optimization: Algorithms and Applications (Nonconvex Optimization and Its Applications)
A neural network approach to multiobjective and multilevel programming problems
Computers & Mathematics with Applications
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A differential evolution approach for solving constrained min-max optimization problems
Expert Systems with Applications: An International Journal
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
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Bi-level linear programming is a technique for modeling decentralized decision. It consists of the upper-level and lower-level objectives. This paper attempts to develop an efficient method based on particle swarm optimization (PSO) algorithm with swarm intelligence. The performance of the proposed method is ascertained by comparing the results with genetic algorithm (GA) using four problems in the literature and an example of supply chain model. The results illustrate that the PSO algorithm outperforms GA in accuracy.