Swarm intelligence is concerned with the design of intelligent multi-agent systems by taking inspiration from the collective behaviour of natural species such bees, ants, flocks of birds or schools of fish. Swarm research essentially falls into three categories:
- Swarm intelligence algorithms are modified in order to improve their performance in terms of convergence, algorithm efficacy and accuracy.
- Modifying the algorithm depending on a specific problem.
- Modifying/designing an algorithm so that it can applied to addressing a wide range of applications.
Swarm intelligence can be applied to a variety of fields in fundamental research, engineering, industries and social sciences.
The main objective of this special issue is to present a collection of high-quality research articles that address the broad challenges and solutions in industrial problems with application aspects of swarm intelligence, and to reflect emerging trends in state-of-the-art algorithms.
Suitable topics include, but are not limited to, the following:
- Materials acquisition
- Medical dataset classification
- Heating system planning
- Dynamic control
- Train schedule timetabling
- Shape optimisation
- Telecommunication network design
- Problems from computational biology
- Software project planning and scheduling
- Mechanical engineering design problems
- Resource optimisation (human, financial, machinery)
- Noise control
- Optimisation of power flows
- Sensor network localisation
Important DatesSubmission of manuscripts: 1 August, 2017
Notification to authors: 1 November, 2017
Final versions due: 10 February, 2018
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