Calls for papers


International Journal of Swarm Intelligence
International Journal of Swarm Intelligence


Special Issue on: "Advanced Nature-Inspired Optimisation Techniques for Engineering Applications"

Guest Editors:
Dr. Soniya Lalwani, Rajasthan Technical University, India
Prof. Anand Nayyar, Duy Tan University, Vietnam
Prof. Rajesh Kumar, Malaviya National Institute of Technology, India

Nature has produced several efficient processes which offer solutions for complex and dynamic real-world problems. These efficient processes, namely nature-inspired optimisation techniques, include evolutionary algorithms, swarm intelligence, artificial neural networks, artificial life, artificial immune systems, fractal geometry, DNA computing, quantum computing, and many more.

Real-world optimisation problems are usually complex, large-scale and NP-hard. They not only contain the terms of constraints, single/multiple objectives, but also involve modelling that evolves continuously. Hence, their solutions require further advancements in available nature-inspired optimisation techniques.

The aim of this special issue is to facilitate and enhance the information available in the field of nature-inspired algorithms, including that related to the development of advanced nature-inspired optimisation algorithms, and/or to the application of improved variants of existing ones for solving real-world complex problems.

Subject Coverage
Suitable topics include, but are not limited, to the following:

  • Latest nature-inspired algorithms for complex, constrained or multi-objective numerical optimisation problems, including
  • Spider Monkey Optimization (SMO)
  • Teaching-learning-based optimisation (TLBO) algorithm
  • Flower pollination algorithm (FPA)
  • Cat swarm optimisation (CSO) algorithm
  • League championship algorithm (LCA)
  • Anarchic society optimisation (ASO) algorithm
  • Cuckoo optimisation algorithm (COA)
  • Crow search algorithm (CSA)
  • Dragonfly algorithm (DA)
  • Ant lion optimiser (ALO) algorithm
  • Krill herd algorithm (KHA)
  • Grey wolf optimisation (GWO) algorithm
  • Shark smell optimisation (SSO) algorithm
  • Gradient evolution (GE) algorithm
  • Moth-flame optimisation (MFO) algorithm
  • Hybrid algorithms
  • Parallel implementation of nature-inspired algorithms
  • Real-world implications

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper).

All papers are refereed through a peer review process.

All papers must be submitted online. To submit a paper, please read our Submitting articles page.

If you have any queries concerning this special issue, please email Soniya Lalwani at, Prof. Anand Nayyar at or Prof. Rajesh Kumar at

Important Dates

Manuscripts due by: 15 March, 2019