A new method for decision making in multi-objective optimization problems

Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-dominated solutions, a Pareto set. Although it is very interesting to know the non-dominated solutions, an additional criterion is needed to select one solution to be deployed. To better support the design process, this paper presents a new method of solving non-linear multi-objective optimization problems by adding a control function that will guide the optimization process over the Pareto set that does not need to be found explicitly. The proposed methodology differs from the classical methods that combine the objective functions in a single scale, and is based on a unique run of non-linear single-objective optimizers.

Flexibility and modeling in business processes: a multi-dimensional relationship

Over the last few years, Business Process Management (BPM) has achieved increasing popularity and dissemination. An analysis of the underlying assumptions of BPM shows that it pursues two apparently contradicting goals: on the one hand it aims at formalising work practices into business process models; on the other hand, it intends to confer flexibility to the organization - i.e. to maintain its ability to respond to new and unforeseen situations. This paper analyses the relationship between formalisation and flexibility in business process modelling by means of an empirical case study of a BPM project in an aircraft maintenance company. A qualitative approach is adopted based on the Actor-Network Theory. The paper offers two major contributions: (a) it illustrates the sociotechnical complexity involved in BPM initiatives; (b) it points towards a multidimensional understanding of the relation between formalization and flexibility in BPM projects.

Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.

Hybrid heuristic-waterfilling game theory approach in MC-CDMA resource allocation

This paper discusses the power allocation with fixed rate constraint problem in multi-carrier code division multiple access (MC-CDMA) networks, that has been solved through game theoretic perspective by the use of an iterative water-filling algorithm (IWFA). The problem is analyzed under various interference density configurations, and its reliability is studied in terms of solution existence and uniqueness. Moreover, numerical results reveal the approach shortcoming, thus a new method combining swarm intelligence and IWFA is proposed to make practicable the use of game theoretic approaches in realistic MC-CDMA systems scenarios. The contribution of this paper is twofold: (i) provide a complete analysis for the existence and uniqueness of the game solution, from simple to more realist and complex interference scenarios; (ii) propose a hybrid power allocation optimization method combining swarm intelligence, game theory and IWFA. To corroborate the effectiveness of the proposed method, an outage probability analysis in realistic interference scenarios, and a complexity comparison with the classical IWFA are presented. (C) 2011 Elsevier B.V. All rights reserved.

A multi-locus approach to barcoding in the Anopheles strodei subgroup (Diptera: Culicidae)

Abstract Background The ability to successfully identify and incriminate pathogen vectors is fundamental to effective pathogen control and management. This task is confounded by the existence of cryptic species complexes. Molecular markers can offer a highly effective means of species identification in such complexes and are routinely employed in the study of medical entomology. Here we evaluate a multi-locus system for the identification of potential malaria vectors in the Anopheles strodei subgroup. Methods Larvae, pupae and adult mosquitoes (n = 61) from the An. strodei subgroup were collected from 21 localities in nine Brazilian states and sequenced for the COI, ITS2 and white gene. A Bayesian phylogenetic approach was used to describe the relationships in the Strodei Subgroup and the utility of COI and ITS2 barcodes was assessed using the neighbor joining tree and “best close match” approaches. Results Bayesian phylogenetic analysis of the COI, ITS2 and white gene found support for seven clades in the An. strodei subgroup. The COI and ITS2 barcodes were individually unsuccessful at resolving and identifying some species in the Subgroup. The COI barcode failed to resolve An. albertoi and An. strodei but successfully identified approximately 92% of all species queries, while the ITS2 barcode failed to resolve An. arthuri and successfully identified approximately 60% of all species queries. A multi-locus COI-ITS2 barcode, however, resolved all species in a neighbor joining tree and successfully identified all species queries using the “best close match” approach. Conclusions Our study corroborates the existence of An. albertoi, An. CP Form and An. strodei in the An. strodei subgroup and identifies four species under An. arthuri informally named A-D herein. The use of a multi-locus barcode is proposed for species identification, which has potentially important utility for vector incrimination. Individuals previously found naturally infected with Plasmodium vivax in the southern Amazon basin and reported as An. strodei are likely to have been from An. arthuri C identified in this study.

Texture analysis by multi-resolution fractal descriptors

This work proposes a novel texture descriptor based on fractal theory. The method is based on the Bouligand- Minkowski descriptors. We decompose the original image recursively into four equal parts. In each recursion step, we estimate the average and the deviation of the Bouligand-Minkowski descriptors computed over each part. Thus, we extract entropy features from both average and deviation. The proposed descriptors are provided by concatenating such measures. The method is tested in a classification experiment under well known datasets, that is, Brodatz and Vistex. The results demonstrate that the novel technique achieves better results than classical and state-of-the-art texture descriptors, such as Local Binary Patterns, Gabor-wavelets and co-occurrence matrix.