New Usage of SOM for Genetic Algorithms
نویسندگان
چکیده
Self-Organizing Map (SOM) is an unsupervised learning neural network and it is used for preserving the structural relationships in the data without prior knowledge. SOM has been applied in the study of complex problems such as vector quantizations, combinatorial optimization, and pattern recognition. This paper proposes a new usage of SOM as a tool for schema transformation hoping to achieve more efficient genetic process. Every offspring is transformed into an isomorphic neural network with more desirable shape for genetic search. This helps genes with strong epistasis to stay close together in the chromosome. Experimental results showed considerable improvement over previous results.
منابع مشابه
Creation of Text Document Matrices and Visualization by Self-Organizing Map
In the paper, text mining and visualization by self-organizing map (SOM) are investigated. At first, textual information must be converted into numerical one. The results of text mining and visualization depend on the conversion. So, the influence of some control factors (the common word list and usage of the stemming algorithm) on text mining results, when a document dictionary is created, is ...
متن کاملA New Approach to Solve N-Queen Problem with Parallel Genetic Algorithm
Over the past few decades great efforts were made to solve uncertain hybrid optimization problems. The n-Queen problem is one of such problems that many solutions have been proposed for. The traditional methods to solve this problem are exponential in terms of runtime and are not acceptable in terms of space and memory complexity. In this study, parallel genetic algorithms are proposed to solve...
متن کاملA New Approach of Backbone Topology Design Used by Combination of GA and PSO Algorithms
A number of algorithms based on the evolutionary processing have been proposed forcommunication networks backbone such as Genetic Algorithm (GA). However, there has beenlittle work on the SWARM optimization algorithms such as Particle Swarm Optimization(PSO) for backbone topology design. In this paper, the performance of PSO on GA isdiscussed and a new algorithm as PSOGA is proposed for the net...
متن کاملAn Efficient Genetic Algorithm for Task Scheduling on Heterogeneous Computing Systems Based on TRIZ
An efficient assignment and scheduling of tasks is one of the key elements in effective utilization of heterogeneous multiprocessor systems. The task scheduling problem has been proven to be NP-hard is the reason why we used meta-heuristic methods for finding a suboptimal schedule. In this paper we proposed a new approach using TRIZ (specially 40 inventive principles). The basic idea of thi...
متن کاملA New Mathematical Model in Cell Formation Problem with Consideration of Inventory and Backorder: Genetic and Particle Swarm Optimization Algorithms
Cell Formation (CF) is the initial step in the configuration of cell assembling frameworks. This paper proposes a new mathematical model for the CF problem considering aspects of production planning, namely inventory, backorder, and subcontracting. In this paper, for the first time, backorder is considered in cell formation problem. The main objective is to minimize the total fixed and variable...
متن کامل