In this paper we consider a problem of generation by cellular automata of high quality pseudorandom sequences useful in cryptography. For this purpose one dimensional nonuniform cellular automata is used. The quality of pseudorandom sequences generated by cellular automata depends on collective behavior of rules assigned to the cellular automata cells. Genetic algorithm is used to find suitable...

In recent years Cellular Manufacturing has become an effective tool for improving productivity. Attainment of full benefits of Cellular Manufacturing depends firstly on the design of the machine cells and part families, secondly on the method of operations which takes full advantage of cell properties. Inappropriate methods of loading and scheduling can even lead to the failure of the Cellular ...

Synthesis of cellular automata is an important area of modeling and describing complex systems. Large amounts of combinations and candidate solutions render the usage of deterministic approaches impractical and thus nondeterministic optimization methods have to be employed. Two of the typical evolutionary approaches to synthesizing cellular automata are the evolution of a single automaton and a...

This paper introduces a new cellular genetic algorithm for solving multiobjective continuous optimization problems. Our approach is characterized by using an external archive to store nondominated solutions and a feedback mechanism in which solutions from this archive randomly replace existing individuals in the population after each iteration. The result is a simple and elitist algorithm calle...

How does evolution produce sophisticated emergent computation in systems composed of simple components limited to local interactions? To model such a process, we used a genetic algorithm (GA) to evolve cellular automata to perform a computational task requiring globally-coordinated information processing. On most runs a class of relatively unsophisticated strategies was evolved, but on a subset...

For dynamic optimization problems, the aim of an effective optimization algorithm is both to find the optimal solutions and to track the optima over time. In this paper, we advanced two kinds of cellular genetic algorithms inspired by the density dependence scheme in ecological system to solving dynamic optimization problems. Two kinds of improved evolution rules are proposed to replace the rul...

Maintenance of cell efficiency in Cellular Manufacturing System is important. Once the cell is formed, new parts come naturally for processing. These parts may not be completely processed in a single manufacturing group and need different machines for processing. This paper presents a procedure for allocating new parts to machine groups using the concept of composite parts. Initially for each o...

In this paper we study a number of issues related to the design of a cellular genetic algorithm (cGA) for multiobjective optimization. We take as an starting point an algorithm following the canonical cGA model, i.e., each individual interacts with those ones belonging to its neighborhood, so that a new individual is obtained using the typical selection, crossover, and mutation operators within...