Issue: 2024/Vol.34/No.1, Pages 149-174
A SOLUTION METHOD FOR STOCHASTIC MULTILEVEL PROGRAMMING PROBLEMS. A SYSTEMATIC SAMPLING EVOLUTIONARY APPROACH
Natnael Nigussie Goshu
, Semu Mitiku Kassa
Cite as: N. N. Goshu, S. M. Kassa. A solution method for stochastic multilevel programming problems. A systematic sampling evolutionary approach. Operations Research and Decisions 2024: 34(1), 149-174. DOI 10.37190/ord240108
Abstract
Stochastic multilevel programming is a mathematical programming problem with some given number of hierarchical levels of decentralized decision makers and having some kind of randomness properties in the problem definition. The introduction of some randomness property in its hierarchical structure makes stochastic multilevel problems computationally challenging and expensive. In this article, a systematic sampling evolutionary method is adapted to solve the problem. The solution procedure is based on realization of the random variables and systematic partitioning of each hierarchical level’s decision space for searching an optimal reaction. The search goes sequentially upwards starting from the bottom up through the top hierarchical level problem. The existence of solution and convergence of the solution procedure is shown. The solution procedure is implemented and tested on some selected deterministic test problems from literature. Moreover, the proposed algorithm can be used to solve stochastic multilevel programming problems with additional complexity in their problem definition.
Keywords: multilevel programming, stochastic programming, Stackelberg equilibrium, sample average approximation, systematic sampling, particle swarm optimization
Received: 21 January 2023 Accepted: 12 January 2024
Published online: 28 March 2024