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The use of swarm algorithm in obtaining Pareto solution when applying the proposed model can be investigated as a further study.
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Through the use of the swarm algorithm it is possible to search for solutions in a large feature space and achieve optimality in terms of energy, economy and pollutant emission simultaneously.
A fleet of trucks using a swarm algorithm could increase throughput in cargo yards; a trusted peer-to-peer ledger on the blockchain architecture could revolutionize the meaning of compliance in the industry, and a host of wearables, mobile robots, as well as machine learning approaches, could rapidly fasten the pace of order fulfilment.
Finally, on terms of design variables and constraints, optimization of the beams using particle swarm algorithm is presented with an example.
To make full use of swarm intelligence, a modified harmony search algorithm (MHS) is proposed and applied to add cooperation among swarms in IFFOA.
This new algorithm incorporates fish-swarm optimization [ 18], which is a widely used particle swarm algorithm that is based on swarm intelligence.
The optimization is performed using the particle swarm algorithm.
Thus, to define the behaviors that regulate the search strategy is another important part of a swarm algorithm.
Parameters of multiple stabilizers are designed in coordination by using a newly appeared method of optimisation artificial fish swarm algorithm.
The use of genetic and particle swarm algorithms in the design of techno-economically optimum shell-and-tube heat exchangers is demonstrated.
For the optimization of the lateral supports two evolutionary algorithms are used, genetic algorithm and particle swarm algorithm.
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