Sharif Digital Repository

Artificial Immune System algorithms use antibodies which fully specify the solution of an optimization, learning, or pattern recognition problem. By being restricted to fully specified antibodies, an AIS algorithm can not make use of schemata or classes of partial solutions. This paper presents a symbiotic artificial immune system (SymbAIS) algorithm which is an extension of CLONALG algorithm. It uses partially specified antibodies and gradually builds up building blocks of suitable sub-antibodies. The algorithm is compared with CLONALG on multimodal function optimization and combinatorial optimization problems and it is shown that it can solve problems that CLONALG is unable to solve.... 

Recombination in the Genetic Algorithm (GA) is supposed to extract the component characteristics from two parents and reassemble them in different combinations hopefully producing an offspring that has the good characteristics of both parents. Symbiotic Combination is formerly introduced as an alternative for sexual recombination operator to overcome the need of explicit design of recombination operators in GA all. This paper presents an optimization algorithm based on using this operator in Tabu Search. The algorithm is benchmarked on two problem sets and is compared with standard genetic algorithm and symbiotic evolutionary adaptation model, showing success rates higher than both cited... 

Evolutionary Algorithms are vastly used in development of rule based classifier systems in data mining where the rule base is usually a set of If-Then rules and an evolutionary trait develops and optimizes these rules. Genetic Algorithm is usually a favorite solution for such tasks as it globally searches for good rule-sets without any prior bias or greedy force, but it is usually slow. Also, designing a good genetic algorithm for rule base evolution requires the design of a recombination operator that merges two rule bases without disrupting the functionalities of each of them. To overcome the speed problem and the need to design recombination operator, this paper presents a novel algorithm... 

Recombination in Genetic Algorithms (GA) is supposed to extract the component characteristics from two parents and reassemble them in different combinations, hopefully producing an offspring that has the good characteristics of both parents, and this requires explicit chromosome and recombination, operator by design. This paper presents a novel evolutionary approach based on symbiogenesis which uses symbiotic combination instead of sexual recombination, and by using this operator, it requires no domain knowledge for chromosome or combination operator design. The algorithm is benchmarked on three problem sets: combinatorial optimization category, deceptive problems, and fully deceptive... 

Genetic Algorithms are vastly used in development of rule based classifier systems in data mining. In such tasks, the rule base is usually a set of If-Then rules and the rules are developed using an evolutionary trait. GA is usually a good solution for such tasks as it globally searches for good rule-sets without any prior bias or greedy force, but it is usually slow. This paper presents a novel algorithm for rule base generation based on natural process of symbiogenesis. The algorithm uses symbiotic combination operator instead of traditional sexual recombination operator of genetic algorithms. The new algorithm is compared with genetic algorithm on some globally used benchmarks and it is...