8 resultados para 1207 Investigación operativa

em Universidade Complutense de Madrid


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One of the main challenges of fuzzy community detection problems is to be able to measure the quality of a fuzzy partition. In this paper, we present an alternative way of measuring the quality of a fuzzy community detection output based on n-dimensional grouping and overlap functions. Moreover, the proposed modularity measure generalizes the classical Girvan–Newman (GN) modularity for crisp community detection problems and also for crisp overlapping community detection problems. Therefore, it can be used to compare partitions of different nature (i.e. those composed of classical, overlapping and fuzzy communities). Particularly, as is usually done with the GN modularity, the proposed measure may be used to identify the optimal number of communities to be obtained by any network clustering algorithm in a given network. We illustrate this usage by adapting in this way a well-known algorithm for fuzzy community detection problems, extending it to also deal with overlapping community detection problems and produce a ranking of the overlapping nodes. Some computational experiments show the feasibility of the proposed approach to modularity measures through n-dimensional overlap and grouping functions.

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In this position paper we propose a consistent and unifying view to all those basic knowledge representation models that are based on the existence of two somehow opposite fuzzy concepts. A number of these basic models can be found in fuzzy logic and multi-valued logic literature. Here it is claimed that it is the semantic relationship between two paired concepts what determines the emergence of different types of neutrality, namely indeterminacy, ambivalence and conflict, widely used under different frameworks (possibly under different names). It will be shown the potential relevance of paired structures, generated from two paired concepts together with their associated neutrality, all of them to be modeled as fuzzy sets. In this way, paired structures can be viewed as a standard basic model from which different models arise. This unifying view should therefore allow a deeper analysis of the relationships between several existing knowledge representation formalisms, providing a basis from which more expressive models can be later developed.

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Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local search variations: a first improvement descent using stochastic information, a tabu search using stochastic information when updating the incumbent solution, and a tabu search using stochastic information when selecting moves based on a list of moves determined through a proxy evaluation. In particular, the three local search variations are designed to utilize stochastic information in the form of sampled scenarios. The results indicate that adding local search using stochastic information to the existing heuristics can further reduce operating costs for shipping companies by 0.5–2 %. While the existing heuristics could produce structurally different solutions even when using similar stochastic information in the search, the appended local search methods seem able to make the final solutions more similar in structure.

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The aggregation operator have been considered from a computable point of view. The important condition that the computation is friendly when portions of data are inserted o deleted to the list of values to aggregate is considered.

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In this paper we examine the time T to reach a critical number K0 of infections during an outbreak in an epidemic model with infective and susceptible immigrants. The underlying process X, which was first introduced by Ridler-Rowe (1967), is related to recurrent diseases and it appears to be analytically intractable. We present an approximating model inspired from the use of extreme values, and we derive formulae for the Laplace-Stieltjes transform of T and its moments, which are evaluated by using an iterative procedure. Numerical examples are presented to illustrate the effects of the contact and removal rates on the expected values of T and the threshold K0, when the initial time instant corresponds to an invasion time. We also study the exact reproduction number Rexact,0 and the population transmission number Rp, which are random versions of the basic reproduction number R0.

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Large scale disasters, such as the one caused by the Typhoon Haiyan, which devastated portions of the Philippines in 2013, or the catastrophic 2010 Haiti earthquake, which caused major damage in Port-au-Prince and other settlements in the region, have massive and lasting effects on populations. Nowadays, disasters can be considered as a consequence of inappropriately managed risk. These risks are the product of hazards and vulnerability, which refers to the extent to which a community can be affected by the impact of a hazard. In this way, developing countries, due to their greater vulnerability, suffer the highest costs when a disaster occurs. Disaster relief is a challenge for politics, economies, and societies worldwide. Humanitarian organizations face multiple decision problems when responding to disasters. In particular, once a disaster strikes, the distribution of humanitarian aid to the population affected is one of the most fundamental operations in what is called humanitarian logistics. This term is defined as the process of planning, implementing and controlling the effcient, cost-effective ow and storage of goods and materials as well as related information, from the point of origin to the point of consumption, for the purpose of meeting the end bene- ciaries' requirements and alleviate the suffering of vulnerable people, [the Humanitarian Logistics Conference, 2004 (Fritz Institute)]. During the last decade there has been an increasing interest in the OR/MS community in studying this topic, pointing out the similarities and differences between humanitarian and business logistics, and developing models suited to handle the special characteristics of these problems. Several authors have pointed out that traditional logistic objectives, such as minimizing operation cost, are not the most relevant goals in humanitarian operations. Other factors, such as the time of operation, or the design of safe and equitable distribution plans, come to the front, and new models and algorithms are needed to cope with these special features. Up to six attributes related to the distribution plan are considered in our multi-criteria approach. Even though there are usually simple ways to measure the cost of an operation, the evaluation of some other attributes such as security or equity is not easy. As a result, several attribute measures are proposed and developed, focusing on different aspects of the solutions. Furthermore, when metaheuristic solution methods are used, considering non linear objective functions does not increase the complexity of the algorithms significantly, and thus more accurate measures can be utilized...

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In this chapter we review several properties of Atanassov’s intuitionistic fuzzy relations, recalling the main concepts related to Atanassov’s intuitionistic fuzzy relations and the main properties that can be demanded to such conepts. We also consider the use of Atanassov’s operators over such relations.

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The demand of highest quality foods in terms of taste and their properties preservation without the use of additives is constantly increasing. Consequently, new approaches to food processing have been developed, as for example high-pressure technology which has proven to be very valuable because it allows to maintain good properties of food like some vitamins and, at the same time, to reduce some undesirable bacteria. This technology avoids the use of high temperatures during the process (not like Pasteurization), which may have adverse effect on some nutritional properties of the food, its flavour, etc. The models for some enzymatic inactivations, which depend on the pressure and temperature profiles are presented. This work deals with the optimization of the inactivation of certain enzymes when high pressure treatment on food processing is applied. The optimization algorithms will minimize the inactivation not only of a certain isolated enzyme but also to several enzymes that can be involved simultaneously in the high-pressure process.