In this paper, we consider the problem of finding a minimum common par-tition of two strings (MCSP). The problem has its application in genome comparison. As it is an NP-hard, discrete combinatorial optimization prob-lem, we employ a metaheuristic technique, namely, MAX-MIN ant system to solve this

We survey the current techniques to cope with the problem of string matching allowing errors. This is becoming a more and more relevant issue for many fast growing areas such as information retrieval and computational biology. We focus on online searching and mostly on edit distance, explaining

Ant algorithms are multi-agent systems in which the behavior of each single agent, called artificial ant or ant for short in the following, is inspired by the behavior of real ants. Ant algorithms are one of the most successful examples of swarm intelligent systems [3], and have been applied

Ant System is a general purpose algorithm inspired by the study of the behavior of Ant Colonies. It is based on a cooperative search paradigm that is applicable to the solution of combinatorial optimization problems. In this paper we introduce MAX --MIN Ant System, an improved version of basic Ant

A new and conceptually simple data structure, called a suffix array, for on-line string searches is intro-duced in this paper. Constructing and querying suffix arrays is reduced to a sort and search paradigm that employs novel algorithms. The main advantage of suffix arrays over suffix trees

In this paper we present the application of MAX-MIN Ant System to the Quadratic Assignment Problem. MAX-MIN Ant System is an improvement over Ant System, an earlier proposed algorithm of Ant Colony Optimization. The computational results show that very high solutions quality can be obtained using

Growth of distributed systems has attained unstoppable momentum. If we better understood how to think about, analyze, and design distributed systems, we could direct their implementation with more confidence.

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With this paper, we contribute to the understanding of ant colony optimization (ACO) algorithms by formally analyz-ing their runtime behavior. We study simple MAX-MIN ant systems on the class of linear pseudo-Boolean functions de-fined on binary strings of length n. Our investigations point out how

architecture. It examines in depth the principles of modern protection architectures and the relation between capability systems and access control list systems, and ends with a brief analysis of protected subsystems and protected objects. The reader who is dismayed by either the prerequisites or the level