Imperialist Competitive Algorithm: Sociopolitical Optimization, Essays (university) of Computer Programming

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T.C.

GAZİ UNIVERSITY

ENGINEERING FACULTY

INDUSTRIAL ENGINEERING DEPARTMENT

THE IMPERIALIST COMPETITIVE ALGORITHM

Selin SAMAR | Computer Programming I | 23.05.

201122032 | Section - 1

Imperialist Competitive Algorithm

The concept of algorithm means a process or set of rules to be followed in calculations or other

problem-solving operations, especially by a computer. The algorithms are sets of instructions

designed to perform a specific task, such as multiplying two numbers.

Before defining the Imperialist Competitive Algorithm (ICA), the concepts of imperialism and

imperialist should be known. Lexical meaning of imperialism is a system which a country rules

other countries, also it can be defined as a policy of extending a country’s power and dominion

especially by direct territorial acquisition or by gaining political and economic control of other

areas or countries. In the meantime imperialist is the adjective form of imperialism, that means

relating to, supporting or practicing imperialism, such like imperialist competitive algorithm.

Frequently, optimization is encountered in various scientific and engineering fields and plays a

very important role in solving problems. In the past decades, classic optimization algorithms

developed comprehensively, based on mathematical inferences. Although being very useful

under limited circumstances, they remain dysfunctional in the real-world optimization.

Imperialist Competitive Algorithm (ICA), is a sociopolitical and metaheuristic algorithm,

inspired by historical imperialism process and competition among imperialists, to capture more

colonies and countries. In computer science, ICA is a computational method that is used to solve

many types of complex optimization problems.

The imperialist competitive algorithm (ICA) was proposed by Atashpaz-Gargari and Lucas in

2007, inspired by sociopolitical processes of imperialistic competition of human beings in the

real world. After this proposition, the ICA was extensively investigated and widely applied in

various domains, such as electrical power system optimization, neural network training, data

clustering, facility layout problems, minimal spanning tree problem and so on. Also there were

always improvements and modifications on ICA over the years according to the type of problem

and regarding some sort of lacknesses of the algorithm from the perspective of the problem.

Imperialist Competitive Algorithm (ICA), is a sociopolitical and metaheuristic algorithm,

inspired by historical imperialism process and competition among imperialists, to capture more

colonies and countries. In computer science, ICA is a computational method that is used to solve

many types of complex optimization problems.

Specifically, ICA can be thought of as the social counterpart of genetic algorithms (GAs). ICA is

the mathematical model and computer simulation of human social evolution, while GAs is based

on the biological evolution of species.

gradually brings about a decrease in the power of weaker empires and an increase in the power

of more powerful ones. The imperialistic competition is modeled by picking some (usually one)

of the colonies of the weakest empire and making a competition among all empires to possess

these (this) colonies. The above steps continue until a stop condition is satisfied by reaching to

an acceptable suboptimal solution.

Basic Imperialist Competitive Algorithm

The ICA simulates the process of competition between empires in human society. It starts with

a randomly generated initial population of size N. The cost of each country is calculated by the

equation specific for the problem to be optimized. Then, countries are divided into imperialists

and colonies. Imperialists are the best countries in the population, and colonies are the others

left.

The competitive behavior between the empires is the core of the ICA. In this stage, all empires

try to occupy colonies from others. Firstly, the total cost of every empire is calculated and

normalized according to the formulas , where the T.C. n

and the N.T.C. n

stand for the total cost

and the normalized total cost of the n th empire, respectively, and the ξ is a little positive

number, whose value determines the role of the colonies in determining the total cost of the

empire.

T.C.n=Cost(imperialistn)+ξ⋅mean{Cost(colonies of empiren)}

N.T.C.n=T.C.n−maxi{T.C.i}

The weakest colony of the weakest empire is picked out. Other empires try to obtain it through

competition. The success probability of each empire is given by the formula below and form the

vector P as the second formula expresses. A vector R with the same size as P whose elements are

uniformly distributed random numbers is created as the third formula. Then vector D is created

by subtracting R from P. The empire whose relevant index in D is maximized will obtain the

mentioned colony at the end.

PPn= ∣∣∣∣

N.T.C.n∑Nimpi= 1 N.T.C.i ∣∣∣∣

P=[ pP 1 ,pP 2 ,pP 3 ,⋯,pPNimp]

R=[ r 1 ,r 2 ,r 3 ,⋯,rNimp], where ri∼U( 0 , 1 ) and 1 ≤i≤Nimp

D=P−R=[ D 1 ,D 2 ,D 3 ,⋯,DNimp]=[ pP 1 −r 1 ,pP 2 −r 2 ,pP 3 −r 3 ,⋯,pPNimp−rNimp]

The competition proceeds until the termination condition is met. The weak empire gradually

loses its colonies and the mighty empire occupies more and more colonies. The empire loses all

its colonies will be collapsed.

The Pseudo Code of The Basic Imperialist Competitive Algorithm (ICA)

References

• https://study.com/academy/lesson/what-is-an-algorithm-definition-examples.html
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• https://www.britannica.com/topic/imperialism
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• file:///C:/Users/user/Downloads/Imperialist_Competitive_Algorithm_and_its_Applicat%20(

).pdf

• https://www.mdpi.com/1999-4893/7/2/229/htm