Computers process information and make decisions. Until recently, the decisions they made were not complex, but due to the incessant technological advances that are taking place, systems based on artificial intelligence are achieving levels of competence in decision-making that in many contexts equal or surpass those of humans. These are autonomous decision-making systems that, although they can increase the capacity and efficiency of people in their fields of action, they could also replace them, something that is of concern to society as a whole. Avoiding dysfunctions in these systems is a priority social, scientific and technological objective, which requires theoretical models that include all the richness and variety of decision problems, that precisely define the elements that characterize them and that address the ethical principles that should guide their operation. This article describes each of these aspects in separate sections.

As it is well known, in spite of having small dimensions, there are daily manysituations that require the solution of a decision-making problem: eating, streetscrossing, assessments, shopping and so on. Generally, the way of working onthese types of problems depends on how the information used to evaluate eachalternative is provided and represented, as for instance is the case with: crisp values, fuzzy values, Pythagorean values, etc. In this way, different very wellknownmethods have been developed and modified to help to solve this kind ofproblems. Among them, the following may be remarked: AHP, PROMETHEE,ELECTRE, VIKOR, TOPSIS. But there are many other. This paper shows howto apply the so-called Reference Ideal Method (RIM), previously developed bythe authors, when Pythagorean Fuzzy numbers are used to evaluate eachalternative. The paper shows how to solve a decision-making problem throughthe proposed method using such kind of fuzzy numbers and, in order to showhow to practically apply the RIM method, an illustrative example is provided.

At present, there is a figure of more than 500 thousand houses and 42 thousand classrooms of public schools without electricity in rural and indigenous zones in Mexico. This is due to the fact that they are not connected to the electricity distribution network and as a consequence are the ones that are most in need of electrification projects. Taking this problem into account, this work models and applies a Fuzzy AHP-TOPSIS multicriteria decision method to select the most appropriate electrification system in a rural area located in the south of Mexico. The AHP method is used to calculate the weights and the TOPSIS method is used to obtain the ranking of the alternatives. To carry out this study, a group of three experts in the Mexican energy field who selected a survey were selected. Data were obtained through the corresponding authorities and the families that make up the community. As a result, it was found that a photovoltaic system of 1 kWp isolated was the best alternative to supply electricity to each of the 300 families that make up the community of Cerro Hermoso.

In projectsSánchez-Lozano, J. regardingJiménez-Pérez, J. renewable energyGarcía-Cascales, M. facilities, decisionLamata, M. making is an essential activity that provides greater consistency and viability to the project. The first step that any promoter of such facilities should face is to select an optimal location. To do so, it is necessary to consider all the criteria that influence the decision. However, not all the criteria are equally important, which means that determining their weights is extremely important. The objective of this chapter is to obtain the weights of the decision criteria that influence the location problems of wind farms and solar photovoltaic and thermoelectric plants. For this, a Decision Support System (DSS) has been designed that allows to carry out the extraction of knowledge from an expert group by Fuzzy AHP methodology. Finally, DSS will sort the viable locations based on the importance of the criteria that influence the decision.

Multicriteria decision making methods are essential tools to make decisions in the corporate world. We focus here in the TOPSIS method to analyze the impact that, the way the decision matrix is constructed affects the final results. Two different ways are analized: firstly, the original matrix is considered, and secondly, a variant including two novel alternatives is used. These alternatives are constructed taking into account the range of the corresponding criteria. We made comparisons using a location problem derived from the renewable energy field.

This chapter deals with the study and evaluation of decision criteria that should be considered for the optimal location of solar photovoltaic plants and solar thermal plants with high temperature and which are to be connected to the electricity distribution network. Criteria and subcriteria to be regarded will be of different nature, since environmental, geomorphologic, location, and strictly climatic criteria will all be considered, some of which are dependent on the technology being installed. Thus, we consider as possible alternatives the optimal locations and we will begin with a set of criteria, which must be evaluated for each of the possible alternatives for such a purpose, and includes both quantitative as well as qualitative information. As vaguely implied linguistic variables and numeric values have to be employed due to this disparity in the nature of the information, we will model the weights of the criteria by triangular fuzzy numbers. In order to reflect this and to carry out the extraction of knowledge a survey based on the fuzzy AHP methodology will be elaborated and sent to experts. In this way it will be possible to obtain the weights of the considered criteria for further evaluation of the alternatives.

The requirements to satisfy the energy needs of today without compromising those of future generations have forced humans to adopt rules that permit a better use of the available resources, of which the sun is an inexhaustible energy source. Amongst the energy sources that offer the possibility of exploiting the resources offered by the Earth, solar energy has acquired great strength. Photovoltaic energy has presented a major evolution and it is forecasted as being an important contributor to power generation and an alternative to other non-renewable energy sources. The high cost of solar electricity is today the main reason why electricity from photovoltaic systems has not been introduced in a more widespread way. In this context, the aim of this paper is the study and analysis of the decision criteria to be used when searching for the best photovoltaic cell, studying both the criteria that exert most influence or their manufacture (defined by quantitative and qualitative values) and the alternatives which will be the decision problem to be solved; each alternative will correspond to one type of photovoltaic cell. Thus, relevant information has been provided by three experts and the TOPSIS method has been used to aggregate all the information combined with the use of fuzzy sets which will model the use of linguistic labels in the process.

Rank reversal is a phenomenon that occurs when a decision maker, in the process of selecting an alternative from a set of choices, is confronted with new alternatives that were not thought about when the selection process was initiated. It depends on the relationship between this new alternative and the old ones under each criterion. In this paper, we study the rank reversal phenomenon in the TOPSIS method and we propose modifications in the algorithm of Hwang and Yoon in order to solve the problem. Moreover, we present a general demonstration of the proposed modifications in the algorithm, as well as a numerical example to show these modifications.

The ordered weighted averaging operator has been widely studied for its practical use in decision problems. This operator has an associated weights vector with specific properties. Different variants have been developed to obtain it. Among these are those which use the order relationship between the criteria. This paper presents a method to obtain a weights vector, which has as inputs the weights vector obtained by the Borda–Kendall law and the quantified preference relation between the criteria given by the decision maker. Then, through a set of operations, the new weights vector is obtained; this vector is between the weights obtained by the Borda–Kendall law and the weighted average vector. In addition, the paper shows the properties that verify the vectors obtained by this method and its use is illustrated through an example. © 2012 Wiley Periodicals, Inc.

This paper develops an evaluation approach based on the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). When the input for a decision process is linguistic, it can be understood that the output should also be linguistic. For that reason, in this paper we propose a modification of the TOPSIS algorithm which develops the above idea and which can also be used as a linguistic classifier. In this new development, modifications to the classic algorithm have been considered which enable linguistic outputs and which can be checked through the inclusion of an applied example to demonstrate the goodness of the new model proposed.

Most of the time, the input of the decision process is linguistic, but this is not the case for the output. For that reason, we have modified the TOPSIS model to make it so that the output of the process is the same as the input, that is to say linguistic. This proposal will be applied to the process of quality assessment and accreditation of the Industrial Engineering Schools within the Spanish university system.

The Spanish National Agency for Quality Assessment and Accreditation as part of its evaluation activities has established a procedure for evaluating both teaching and institutions, by means of the Institutional Assessment Programme. In this communication we shall focus on the external assessment phase for qualifications in the field of Industrial Engineering and specifically on the structures of the database for a Decision Support System on the universities' rankings. In particular, this paper will focus on obtaining the weight of the criteria and definition of the linguistic labels used in the external assessment phase.

The industrial organization needs to develop better methods for evaluating the performance of its projects. We are interested in the problems related to pieces with differing degrees of dirt. In this direction, we propose and evaluate a maintenance decision problem of maintenance in an engine factory that is specialized in the production, sale and maintenance of medium and slow speed four stroke engines. The main purpose of this paper is to study the problem by means of the analytic hierarchy process to obtain the weights of criteria, and the TOPSIS method as multicriteria decision making to obtain the ranking of alternatives, when the information was given in linguistic terms.

Fuzzy numbers do not always show a completely orderly group as can be done with real numbers. In applications of problems of multi-attribute decision making, when the final valuations are fuzzy, it is very difficult to distinguish the best possible alternative and the ranking of them. This paper develops an evaluation approach based on the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). In this approach, one step that is necessary to take into consideration is that related with the normalization.

This paper presents two methods to obtain the weights in multiattribute decision making, when the only relation between the attributes is the order. The first one is the SMARTER method. The second is the OWA operator and finally the relation between them. The same operation and examples are also given.

Artificial Intelligence (AI) is the science that focuses its study to achieve the understanding of intelligent entities. It is evident that computers that possess intelligence at a human level will have very important repercussions in our daily life. Inside the fields of AI it is necessary to highlight the decision-making, where AI supposes a great help. In this paper, we present a methodology in a decision-making problem where only linguistic information was available. The main purpose of this paper is to present a technique to obtain the weights and the utilities to resolve the multicriteria decision-making when the knowledge about it is linguistic. Thus we can have systems where the input of data in the computer can be of a determined type and the output can be of the same or a different type, making more intelligent computers. The aim of this paper is to present an evaluation model based on a multicriteria decision analysis that offers the "assembly workshop manager" the possibility of expressing its knowledge in a linguistic framework. In this paper the linguistic decision analysis is interpreted in a multicriteria decision-making context.

In this paper, we present a statistical criterion for accepting/rejecting the pairwise reciprocal comparison matrices in the analytic hierarchy process. We have studied the consistency in random matrices of different sizes. We do not agree with the traditional criterion of accepting matrices due to their inflexibility and because it is too restrictive when the size of the matrix increases. Our system is capable of adapting the acceptance requirements to different scopes and consistency necessities. The advantages of our consistency system are the introduction of adaptability in the acceptance criterion and the simplicity of the index we have used, the eigenvalue (λ max ) and the simplicity of the criterion.