CG GS - Academia.edu (original) (raw)

Papers by CG GS

Innovations in Hybrid Intelligent Systems, 2007

In this paper a statistical selection of relevant features is presented. An experiment was design... more In this paper a statistical selection of relevant features is presented. An experiment was designed to select relevant and not redundant features or characterization functions, which allow quantitatively discriminating among different types of complex networks. As well there exist researchers given to the task of classifying some networks of the real world through characterization functions inside a type of complex network, they do not give enough evidences of detailed analysis of the functions that allow to determine if all are necessary ...

Hybrid Artificial Intelligence Systems, 2010

Abstract. In the last years the population of Leon City, located in the state of Guanajuato in Me... more Abstract. In the last years the population of Leon City, located in the state of Guanajuato in Mexico, has been considerably increasing, causing the inhabitants to waste most of their time with public transportation. As a consequence of the demographic growth and traffic bottleneck, users deal with the daily problem of optimizing their travel so that to get to their destination on time. To give a solution to this problem of obtaining an optimized route between two points in a public transportation, a method based on the cultural algorithms ...

The multi-objective optimization methods are traditionally based on Pareto dominance or relaxed f... more The multi-objective optimization methods are traditionally based on Pareto dominance or relaxed forms of dominance in order to achieve a representation of the Pareto front. However, the performance of traditional optimization methods decreases for those problems with more than three objectives to optimize. The decomposition of a multi-objective problem is an approach that transforms a multi-objective problem into many single-objective optimization problems, avoiding the need of any dominance form. This chapter provides a short review of the general framework, current research trends and future research topics on decomposition methods.

In order for a company to be competitive, an indispensable requirement is the efficient managemen... more In order for a company to be competitive, an indispensable requirement is the efficient management of its resources. As a result derives a lot of complex optimization problems that need to be solved with high-performance computing tools. In addition, due to the complexity of these problems, it is considered that the most promising approach is the solution with approximate algorithms; highlighting the heuristic optimizers.

… 2007. CERMA 2007, Jan 1, 2007

Abstract In this paper a statistical selection of relevant features is presented. An experiment w... more Abstract In this paper a statistical selection of relevant features is presented. An experiment was designed to select relevant and not redundant features or characterization functions, which allow quantitatively discriminating among different types of complex networks. As well there exist researchers given to the task of classifying some networks of the real world through characterization functions inside a type of complex network, they do not give enough evidences of detailed analysis of the functions that allow to determine if all are ...

This chapter is focused on the problem of scheduling independent tasks on heterogeneous machines.... more This chapter is focused on the problem of scheduling independent tasks on heterogeneous machines. The main contributions of our work are the following: a linear programming model to compute energy consumption for the execution of independent tasks on heterogeneous clusters, a constructive heuristic based on local search, and a new benchmark set. To assess our approach we compare the performance of two solution methods: a memetic algorithm, based on population search and local search, and a seeded genetic algorithm, based on NSGA-II. A Wilcoxon rank-sum test shows significant differences in the diversity of solutions found but not in hypervolume. The memetic algorithm gets the best diversity for a bigger instance set from the state of the art.

Resumen La optimización es una disciplina fundamental en campos de la ciencia tales como la compu... more Resumen La optimización es una disciplina fundamental en campos de la ciencia tales como la computación, la inteligencia artificial o la investigación de operaciones. El concepto de optimización puede ser definido como el proceso de intentar encontrar la mejor solución posible a un problema de optimización, generalmente en un tiempo limitado.

The most prevalent P2P application today is file sha ring, both among scientific users and the ge... more The most prevalent P2P application today is file sha ring, both among scientific users and the general public. A fundamental process in file sharing systems is the search mechanism. The unstructured nature of real-world largescale complex systems poses a challenge to the search me thods, because global routing and directory services are impractical to implement. This paper presents a new antcolony algorithm, Adaptive Neighboring-Ant Search (AdaNAS), for the semantic query routing problem (SQRP) in a P2P network.

Journal of …, Jan 1, 2009

The Internet is considered a complex network for its size, interconnectivity and rules that gover... more The Internet is considered a complex network for its size, interconnectivity and rules that govern are dynamic, because of constantly evolve. For this reason the search of distributed resources shared by users and online communities is a complex task that needs efficient search method. The goal of this work is to improve the performance of distributed search of information, through analysis of the topological features. In this paper we described a statistical methodology to select a set of topologic metrics that allow to locally distinguish the type of complex network. In this way we use the metrics to guide the search towards nodes with better connectivity. In addition we present an algorithm for distributed search of information, enriched with the selected topological metric. The results show that including the topological metric in the Neighboring-Ant Search algorithm improves its performance 50% in terms of the number of hops needed to locate a set of resources. The methodology described provides a better understanding of why the features were selected and aids to explain how this metric impacts in the search process.

… Computing and Artificial …, Jan 1, 2009

Resumen. En este artículo se aborda un problema clásico muy conocido por su aplicabilidad y compl... more Resumen. En este artículo se aborda un problema clásico muy conocido por su aplicabilidad y complejidad: el empacado de objetos en contenedores (Bin Packing Problem, BPP). Para la solución de BPP se propone un algoritmo genético híbrido de agrupación denominado HGGA-BP. El algoritmo propuesto está inspirado en el esquema de representación de grupos de Falkenauer, el cual aplica operadores evolutivos a nivel de contenedores.

Advances in Intelligent Systems and Computing, 2013

The performance of the algorithms is determined by two elements: efficiency and effectiveness. In... more The performance of the algorithms is determined by two elements: efficiency and effectiveness. In order to improve these elements, statistical information and visualization are key features to analyze and understand the significant factors that affect the algorithm performance. However, the development of automated tools for this purpose is difficult. In this paper a visual diagnosis tool named VisTHAA, which provides researchers statistical and visual information about instances and algorithms, is proposed. Besides, VisTHAA ...

In this paper, we present a new algorithm to route text queries within a P2P network, called Neig... more In this paper, we present a new algorithm to route text queries within a P2P network, called Neighboring-Ant Search (NAS) algorithm. The algorithm is based on the Ant Colony System metaheuristic and the SemAnt algorithm. More so, NAS is hybridized with local environment strategies of learning, characterization, and exploration. Two Learning Rules (LR) are used to learn from past performance, these rules are modified by three new Learning Functions (LF).