Everardo Gutiérrez

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Many problems in AI can be stated as search problems and most of them are very complex to solve. One alternative for these problems are local search methods that have been widely used for tackling difficult optimization problems for which we do not know algorithms which can solve every instance to optimality in a reasonable amount of time. One of the most(More)
In this work, an experimental study to evaluate the parameter vector utility brought by an automated tuning tool, so called Hybrid Automatized Tuning procedure (HATp) is given. The experimental work uses the inertia weight and number of iterations from the algorithm PSO; it compares those parameters from tuning by analogy and empirical studies. The task of(More)
This paper introduces a new algorithm to deal with multi-objective combinatorial and continuous problems. The algorithm is an extension of a previous one designed to deal with single objective com-binatorial problems. The original purpose of the single objective version was to study in a rigorous way the properties the search graph of a particular problem(More)
Many real world problems can be modeled as the shortest common superstring problem. This problem has several important applications in areas such as DNA sequencing and data compression. The shortest common superstring problem (SCS) can be formulated as follows. Given a set of strings S = {s 1 , s 2 , ..., s n } the goal is to find the shortest string N *(More)
This paper presents preliminary results on the comparison of binary and integer based representations for the Base Stations Location (BSL) problem. The simplest model of this problem, which is already NP-complete, is dealt with to compare also different crossover operators. Experimental results support the hypothesis that the integer based representation(More)
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