SCA 2013 Abstracts

Full Papers
Full Papers
Paper Nr: 1
Title:

Fuzzy Optimization Models for Seaside Port Logistics
Authors:

Belén Melián-Batista, Christopher Expósito-Izquierdo, Eduardo Lalla-Ruiz, María Teresa Lamata and J. Marcos Moreno-Vega
Abstract: The main goal of maritime container terminals is to serve the container vessels arriving at port. This means that they must be berthed in a position along the quay, a subset of quay cranes must be assigned to them and work schedules have to be planned for unloading the import containers and loading the export containers onto each container vessel. This work addresses the Tactical Berth Allocation Problem, in which the vessels are assigned to a given berth, and the Quay Crane Scheduling Problem, for which the work schedules of the quay cranes are determined. Due to the fact that the nature of this environment gives rise to inaccurate knowledge about the information related to the incoming vessels, the aforementioned optimization problems are tackled considering fuzzy arrival times for the vessels and fuzzy processing times for the loading/unloading operations.
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Paper Nr: 2
Title:

Decision Support Systems to Obtain Decision Criteria by Fuzzy AHP for Location of Renewable Energy Facilities
Authors:

Juan M. Sanchez-Lozano, Jose Angel Jimenez-Pérez, M. Socorro Garcia-Cascales and M. Teresa Lamata
Abstract: Location of Renewable Energy Facilities will depend on various factors such as environmental, orography location and climatology criteria, which in turn are broken down into sub-criteria that will depend on the technology to locate. The objective of the present paper is to obtain the weights of the decision criteria which influence in the problem of location of renewable energy facilities, especially in wind farms and solar plants (photovoltaic and thermoelectric). To that end a Decision Support System (DSS) has been designed to help the decision-maker to obtain the weights of the criteria involved in this decision. Fuzzy AHP methodology is used with that DSS for the extraction of expert knowledge and to model the vague and imprecise data by triangular fuzzy numbers.
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Paper Nr: 3
Title:

Hierarchical Qualitative Descriptions of Perceptions for Robotic Environments
Authors:

Enrique Muñoz, Takehiko Nakama and E. Ruspini
Abstract: The development and uptake of robotic technologies, outside the research community, has been hindered by the fact that robotic systems are notably lacking in flexibility. Introducing humans in robot teams promises to improve their flexibility. However, the major underlying difficulty in the development of human-robot teams is the inability of robots to emulate important cognitive capabilities of human beings due to the lack of approaches to generate and effectively abstract salient semantic aspects of information and big data sets. In this paper we develop a general framework for information abstraction that allows robots to obtain high level descriptions of their perceptions. These descriptions are represented using a formal predicate logic that emulates natural language structures, facilitating human understanding while it remains easy to interpret by robots. In addition, the proposed formal logic constitutes a precisiation language that generalizes Zadeh's Precisiated Natural Language, providing new tools for the computation with perceptions.
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Paper Nr: 4
Title:

Using a Fuzzy Decision Tree Ensemble for Tumor Classification from Gene Expression Data
Authors:

José M. Cadenas, M. Carmen Garrido, Raquel Martínez, David A. Pelta and Piero P. Bonissone
Abstract: Machine learning techniques are useful tools that can help us in the knowledge extraction from gene expression data in biological systems. In this paper two machine learning techniques are applied to tumor datasets based on gene expression data. Both techniques are based on a fuzzy decision tree ensemble and are used to carry out the classification and selection of features on datasets. The classification accuracies obtained both when we use all genes to classify and when we only use the selected genes are high. However, in this second case the result also increases the interpretability of the solution provided by the technique. Additionally, the feature selection technique provides a ranking of importance of genes and a partitioning of the domains of the genes.
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Paper Nr: 5
Title:

Generalization and Formalization of Precisiation Language with Applications to Human-Robot Interaction
Authors:

Takehiko Nakama, Enrique Muñoz and Enrique Ruspini
Abstract: We generalize and formalize precisiation language by establishing a formal logic as a generalized precisiation language. Various syntactic structures in natural language are incorporated in the syntax of the formal logic so that it can serve as a middle ground between the natural-language-based mode of human communication and the low-level mode of machine communication. As regards the semantics, we establish the formal logic as a many-valued logic, and fuzzy relations are employed to determine the truth values of propositions efficiently. We discuss how the generalized precisiation language can facilitate human-robot interaction.
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