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Update README.md
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Samsomyajit authored Feb 17, 2020
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Expand Up @@ -12,6 +12,10 @@ architecture. An ant colony can be thought of as a swarm whose individual agents
Similarly a flock of birds is a swarm of birds. An immune system is a swarm of cells and
molecules as well as a crowd is a swarm of people . Particle Swarm Optimization (PSO)
Algorithm models the social behaviour of bird flocking or fish schooling . <br>
<p align="center">
<img src="https://github.com/Samsomyajit/Hive-TSP/blob/master/misc/swarm.JPG">
</p>

<h2>PROPOSED APPROACH</h2>
In this work, a particular intelligent behaviour of a honey bee swarm, foraging behaviour, is
considered and a new artificial bee colony (ABC) algorithm simulating this behaviour of real
Expand All @@ -22,7 +26,7 @@ the second half includes the onlookers. For every food source, there is only one
bee. In other words, the number of employed bees is equal to the number of food sources
around the hive. The employed bee whose food source has been exhausted by the bees
becomes a scout. The main steps of the algorithm are given below:<br>
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<h4>Algorithm:</h4>
<b><br>
Send the scouts onto the initial food sources<br>
Expand Down Expand Up @@ -63,4 +67,11 @@ the optimal solutions of the difficult optimization problems can be discovered.
and progress of the real bee swarm depended upon the rapid discovery and efficient utilization
of the best food resources. Similarly the optimal solution of difficult engineering problems is
connected to the relatively fast discovery of “good solutions” especially for the problems that
need to be solved in real time.
need to be solved in real time.<br>
<p align="center">
<img src="https://github.com/Samsomyajit/Hive-TSP/blob/master/misc/tsp1.JPG">
</p>
<br>
<p align="center">
<img src="https://github.com/Samsomyajit/Hive-TSP/blob/master/misc/tsp2.JPG">
</p>

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