Name
Title | ||
|---|---|---|
Society and civilization: An optimization algorithm based on the simulation of social behavior |
Abstract | ||
|---|---|---|
The ability to mutually interact is a fundamental social behavior in all human and insect societies. Social interactions enable individuals to adapt and improve faster than biological evolution based on genetic inheritance alone. This is the driving concept behind the optimization algorithm introduced in this paper that makes use of the intra and intersociety interactions within a formal society and the civilization model to solve single objective constrained optimization problems. A society corresponds to a cluster of points in the parametric space while a civilization is a set of all such societies. Every society has its set of better performing individuals (leaders) that help others to improve through information exchange. This results in the migration of a point toward a better performing point, analogous to an intensified local search. Leaders improve only through an intersociety information exchange that results in the migration of a leader from a society to another. This helps the better performing societies to expand and flourish. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/TEVC.2003.814902 | IEEE Trans. Evolutionary Computation |
Keywords | Field | DocType |
fundamental social behavior,optimization algorithm,intersociety information exchange,society corresponds,insect society,optimization problem,formal society,information exchange,civilization model,intersociety interaction,constrained optimization,local search,social behavior,formal specification,social interaction,pareto,simulation,indexing terms,genetics,genetic algorithm | Social relation,Artificial intelligence,Genetic algorithm,Management science,Civilization,Information exchange,Operations research,Formal specification,Local search (optimization),Machine learning,Pareto principle,Mathematics,Constrained optimization | Journal |
Volume | Issue | ISSN |
7 | 4 | 1089-778X |
Citations | PageRank | References |
147 | 6.17 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| T. Ray | 1 | 357 | 15.32 |
| K. M. Liew | 2 | 214 | 19.27 |