Review of Anaerobic Digestion Modeling and Optimization Using Nature-Inspired Techniques

Anjali Ramachandran, Rabee Rustum, Adebayo J. Adeloye

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)
87 Downloads (Pure)


Although it is a well-researched topic, the complexity, time for process stabilization, and economic factors related to anaerobic digestion call for simulation of the process offline with the help of computer models. Nature-inspired techniques are a recently developed branch of artificial intelligence wherein knowledge is transferred from natural systems to engineered systems. For soft computing applications, nature-inspired techniques have several advantages, including scope for parallel computing, dynamic behavior, and self-organization. This paper presents a comprehensive review of such techniques and their application in anaerobic digestion modeling. We compiled and synthetized the literature on the applications of nature-inspired techniques applied to anaerobic digestion. These techniques provide a balance between diversity and speed of arrival at the optimal solution, which has stimulated their use in anaerobic digestion modeling.
Original languageEnglish
Article number953
Issue number12
Publication statusPublished - 13 Dec 2019


  • anaerobic digestion
  • ant colony optimization
  • firefly algorithm
  • particle swarm optimization
  • genetic algorithm
  • artificial neural network
  • nature-inspired techniques

ASJC Scopus subject areas

  • General Chemical Engineering
  • General Computer Science
  • General Environmental Science


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