A solution method for stochastic multilevel programming problems. A systematic sampling evolutionary approach

Natnael Nigussie Goshu, Semu Mitiku Kassa

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)149-174
Number of pages26
JournalOperations Research and Decisions
Volume34
Issue number1
DOIs
Publication statusPublished - 2024

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research
  • Management of Technology and Innovation

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