Hybrid metaheuristic algorithms in geotechnical engineering

Yung Ming Cheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)


The solutions of many engineering problems can be formulated as the optimized results of a functional. While many engineering problems are governed by a continuous convex optimization process, this is not the case for many geotechnical problems. Many geotechnical problems have irregular solution domains, with the objective function being nonconvex and may not be a continuous function. The presence of multiple local minima is common in many geotechnical problems, and the occurrence of local zones where there is rapid changes in the material parameters is not uncommon. The corresponding governing problems are hence usually NP-type nonconvex optimization problem, and by nature, such NP-type problems with the various constraints pose great difficulty in analysis. While the classical heuristic optimization methods may work well for some of these problems, there are also some practical cases where the classical methods may fail to perform satisfactorily. To maintain a balance between the computation time and accuracy, several hybrid metaheuristic algorithms are proposed by the author which can work well for many practical geotechnical problems. In this chapter, the author will illustrate the basic concept of hybrid metaheuristic algorithms and the applications to some difficult geotechnical problems.
Original languageEnglish
Pages (from-to)277-302
Number of pages26
JournalModeling and Optimization in Science and Technologies
Publication statusPublished - 1 Jan 2016


  • Back analysis
  • Geotechnical engineering
  • Hybrid optimization
  • Slope stability
  • Wave equation

ASJC Scopus subject areas

  • Modelling and Simulation
  • Medical Assisting and Transcription
  • Applied Mathematics


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