90191370 interactive artificial bee colony optimization

8/12/2019 90191370 Interactive Artificial Bee Colony Optimization

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Interactive Artificial Bee Colony (IABC)Optimization

Pei-Wei Tsai, Jeng-Shyang Pan,

Bin-Yih Liao, and Shu-Chuan Chu

[email protected]


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Outline

Introduction

Artificial Bee Colony (ABC) Algorithm

Interactive Artificial Bee Colony (IABC)

Experiments and Experimental Results

Conclusions


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Introduction

Swarm Intelligence employs the collective

behaviors in the animal societies to design

algorithms.

In 2005, Karaboga proposed an Artificial Bee

Colony (ABC), which is based on a particular

intelligent behavior of honeybee swarms.


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Artificial Bee Colony (ABC)

ABC is developed based on inspecting the

behaviors of real bees on finding nectar and

sharing the information of food sources to the

bees in the hive.

Agents in ABC:

The Employed Bee The Onlooker Bee

The Scout


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Artificial Bee Colony (ABC) (2)

The Employed Bee:

It stays on a food source and provides the

neighborhood of the source in its memory.

The Onlooker Bee:It gets the information of food sources from

the employed bees in the hive and select one

of the food source to gathers the nectar.

The Scout:

It is responsible for finding new food, the new

nectar, sources.


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Procedures of ABC:

Initialize (Move the scouts).

Move the onlookers.

Move the scouts only if the counters of theemployed bees hit the limit.

Update the memory

Check the terminational condition


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Movement of the Onlookers

Probability of Selecting a nectar source:

(1)

Pi: The probability of selecting the ithemployed

bee

S: The number of employed beesi: The position of the i

themployed bee

: The fitness value

S

k

k

ii

F

FP

1

iF


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Movement of the Onlookers (2)

Calculation of the new position:

(2)

: The position of the onlooker bee.

t : The iteration number

: The randomly chosen employed bee.

j: The dimension of the solution

: A series of random variable in therange .

ttttx kjijijij 1

ix

k

11,-


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Movement of the Scouts

The movement of the scout bees follows

equation (3).

(3)

r: A random number and

minmaxmin jjjij r

1,0r


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The Employed Bee

The Onlooker Bee The Scout

S

k

k

ii

F

FP

1

Record the best

solution found so far

ttttx kjijijij

1

minmaxmin jjjij r


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Discussion

The movement of the onlookers is limited to

the selected nectar source and the randomly

selected source.

Suppose we find a way to consider more

relations between the employed bees and the

onlookers, we may extend the exploitation

capacity of the ABC algorithm.


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Universal Gravitation

Universal Gravitation is an invisible force

between objects.

(4)

: The gravitational force heads from object 1

to 2.

G: The universal gravitational constant.

m: The mass of the object.

: The separation between the objects.

: The unit vector in the form of equation.

^

212

21

21

12 rr

mmGF

12F

21r

^

21r


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Interactive Artificial Bee Colony (2)

After employing the universal gravitation intoequation (2), it can be reformed as follows:

(5)

By applying equation (5) and simultaneouslyconsidering the gravitation between thepicked employed bee and n selected

employed bees, it can be reformed again intoequation (6).

(6)

][1 ttFttx kjijikijij j

n

k

kjijikijij ttFttx j1

~

][1


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Interactive Artificial Bee Colony (3)

1

2

i

1iF

2iF

2n

n

k

kjijikijij ttFttx j1

~

][1


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Experiments (2)


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Experiments (4)

To apply IABC for solving problems related to

optimization, the number of the considered

employed bee nshould be predetermined.

In these experiments, the number of nis set

to 4.


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Experimental Results

1

100cos100

4000

1

11

2

1

n

i

in

ii i

xxxf


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Experimental Results (3)

n

iii

xxxf1

2

2 102cos10


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Experimental Results (2)

1

1

222

13

1100n

i iii

xxxxf


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Conclusions

IABC is proposed in this paper.

It leads in the concept of universal gravitation

to the movement of onlooker bees in ABC,

and it successfully increases the exploitationability of ABC.

The performance of IABC, ABC and PSO are

compared in the experiments, and the value

of nwith the best reaction is also discussed

and analyzed.


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Thank You for Your Attention.

Any Question?

90191370 interactive artificial bee colony optimization

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