Interactive Artificial Bee Colony (IABC) Optimization

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Interactive Artificial Bee Colony (IABC)
Optimization

• Pei-Wei Tsai, Jeng-Shyang Pan, Bin-Yih Liao,
  and Shu-Chuan Chu
• pwtsai_at_bit.kuas.edu.tw

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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 BeeIt stays on a food source and
  provides the neighborhood of the source in its
  memory.
• The Onlooker BeeIt 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 ScoutIt is responsible for finding new
  food, the new nectar, sources.

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Artificial Bee Colony (ABC) (3)

• Procedures of ABC
• Initialize (Move the scouts).
• Move the onlookers.
• Move the scouts only if the counters of the
  employed 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 ith
  employed bee
• S The number of employed bees
• ?i The position of the ith employed bee
• The fitness value

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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 the range
  .

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Movement of the Scouts

• The movement of the scout bees follows equation
  (3).
• (3)
• r A random number and

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Artificial Bee Colony (ABC) (4)
Record the best solution found so far

• The Employed Bee
• The Onlooker Bee
• The Scout

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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.

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Interactive Artificial Bee Colony

• In Interactive Artificial Bee Colony (IABC), the
  mass in equation (4) is replaced by .
• Euclidean distance is applied for calculating
  .
• The normalization procedure is applied to the
  fitness values we used in equation (4) and the
  normalized fitness values are given as .

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Interactive Artificial Bee Colony (2)

• After employing the universal gravitation into
  equation (2), it can be reformed as follows
• (5)
• By applying equation (5) and simultaneously
  considering the gravitation between the picked
  employed bee and n selected employed bees, it can
  be reformed again into equation (6).
• (6)

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Interactive Artificial Bee Colony (3)
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Experiments

• To analyze the performances, the experiments are
  made with three well-known benchmark functions,
  and the results are compared with ABC and
  Particle Swarm Optimization (PSO).

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Experiments (2)
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Experiments (3)

• Conditions
• Dimension of the solution 50
• Runs for average 30
• Iteration number 5000
• Population size 100

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Experiments (4)

• To apply IABC for solving problems related to
  optimization, the number of the considered
  employed bee n should be predetermined.
• In these experiments, the number of n is set to 4.

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Experimental Results
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Experimental Results (3)
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Experimental Results (2)
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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 exploitation ability
  of ABC.
• The performance of IABC, ABC and PSO are compared
  in the experiments, and the value of n with the
  best reaction is also discussed and analyzed.

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Thank You for Your Attention.

• Any Question?