Integrated Computer-Aided Engineering - Volume 23, issue 3

Article Type: Introduction

DOI: 10.3233/ICA-160524

Citation: Integrated Computer-Aided Engineering, vol. 23, no. 3, pp. 203-, 2016

Authors: Yang, Zhiwei | Emmerich, Michael | Bäck, Thomas | Kok, Joost | Yang, Zhiwei | Emmerich, Michael | Bäck, Thomas | Kok, Joost

Article Type: Research Article

Abstract: This article studies a tri-objective formulation of the inventory routing problem, extending the recently studied bi-objective formulation. As compared to distance cost and inventory cost, which were discussed in previous work, it also considers stockout cost as a third objective. Demand is modeled as a Poisson random variable. State-of-the-art evolutionary multi-objective optimization algorithms and a new method based on swarm intelligence are used to compute approximation of the 3-D Pareto front. A benchmark previously used in bi-objective inventory routing is extended by incorporating a stochastic demand model with an expected value that equals the average demand of the original benchmark. …The results provide insights into the shape of the optimal trade-off surface. Based on this the dependences between different objectives are clarified and discussed. Moreover, the performances of the four different algorithmic methods are compared and due to the consistency in the results, it can be concluded that a near optimal approximation to the Pareto front can be found for problems of practically relevant size. Show more

Keywords: Inventory routing, cooperative swarm algorithm, multi-objective optimization, robust optimization, indicator-based evolutionary algorithms

DOI: 10.3233/ICA-160515

Citation: Integrated Computer-Aided Engineering, vol. 23, no. 3, pp. 205-220, 2016

Authors: Sánchez, Ángel | Moreno, A. Belén | Vélez, Daniel | Vélez, José F.

Article Type: Research Article

Abstract: This paper analyzes both the isolated influence of illumination quality in 2D facial recognition and also the influence of contrast measures in large-scale recognition of low-resolution natural images. First, using the Yale Face Database B, we have shown that by separately estimating the illumination quality of facial images (through a fuzzy inference system that combines average brightness and global contrast of the patterns) and by recognizing the same images using a multilayer perceptron, there exists a nearly-linear correlation between both illumination and recognition results. Second, we introduced a new contrast measure, called Harris Points Measured Contrast (HPMC), which assigns values …of contrast in a more consistent form to images, according to their recognition rate than other global and local compared contrast analysis methods. For our experiments on image contrast analysis, we have used the CIFAR-10 dataset with 60,000 images and convolutional neural networks as classification models. Our results can be considered to decide if it is worth using a given test image, according to its calculated contrast applying the proposed HPCM metric, for further recognition tasks. Show more

Keywords: Image quality assessment, contrast measures, multilayer perceptron, convolutional neural network, 2D face images, CIFAR-10 images

DOI: 10.3233/ICA-160516

Citation: Integrated Computer-Aided Engineering, vol. 23, no. 3, pp. 221-235, 2016

Authors: Prieto, Abraham | Bellas, F. | Trueba, P. | Duro, R.J.

Article Type: Research Article

Abstract: Several engineering optimization problems like routing, freight transportation, exploration, or layout design in their more complex and realistic versions present a series of characteristics that make them very difficult to solve. Among these we find the absence of centralized updated information about all the variables, due to the spread out nature of the problems or lack of appropriate communications, or the dynamism of real-time operation. In fact, most optimization approaches assume that the problems they address are static, meaning that there is an optimal solution that does not change in time, but this is not always the case and there …are problems that require following an optimum that changes in time. Distributed population-based techniques, such as swarms, have provided promising results in this context. They obtain a solution through the concurrent behavior of several adequately constructed processing elements. However, constructing these swarms is not straightforward, and most approaches have just mimicked swarm behaviors found in nature, adapting them to particular problems. The objective of this work is to study the application of a novel evolutionary paradigm, distributed Embodied Evolution (dEE), to obtain heterogeneous swarms that solve a set of realistic problems. In particular, we address here non-separable dynamic fitness landscapes, where interdependences between individuals imply that the contribution provided by one of them to the whole depends on the behavior of the others. This study is carried out applying a canonical version of dEE, which has been developed to generalize the main features of this type of evolutionary paradigm. We analyze the canonical dEE response in a series of scenarios of increasing complexity related to two highly representative dynamic engineering problems: a Dynamic Fleet Size and Mix Vehicle Routing Problem with Time Windows (DFSMVRPTW) and a collective surveillance task with realistic location degradation. Show more

Keywords: Dynamic optimization, Embodied Evolution, cooperative coevolution, heterogeneous populations, multi-agent systems

DOI: 10.3233/ICA-160522

Citation: Integrated Computer-Aided Engineering, vol. 23, no. 3, pp. 237-253, 2016

Authors: del Rey, A. Martín | Encinas, A. Hernández | Vaquero, J. Martín | Dios, A. Queiruga | Sánchez, G. Rodríguez

Article Type: Research Article

Abstract: The main goal of this work is to propose a model for the study and analysis of malware propagation in an industrial critical infrastructure. Specifically, an individual-based mathematical model is introduced and its parameters, variables and equations are explicitly defined and constructed. This model follows the agent based modeling paradigm which makes it extremely suitable for use within the small and heterogeneous environments where individual characteristics of all devices can be captured. The main strengths of this model are its ease of computational implementation (both in hardware and software), and its ability to simulate control measures (which can be of …great help for security system administrators); however, this model strongly depends on a proper identification of the parameters. Show more

Keywords: Critical infrastructure, malware, information security, mathematical modeling, epidemic spreading

DOI: 10.3233/ICA-160518

Citation: Integrated Computer-Aided Engineering, vol. 23, no. 3, pp. 255-268, 2016

Authors: Mencía, Raúl | Sierra, María R. | Mencía, Carlos | Varela, Ramiro

Article Type: Research Article

Abstract: Scheduling problems involving physical machines and human resources are frequent in real production environments. In this paper, we tackle a problem in which a set of tasks must be performed on a set of machines under the assistance of human operators, subject to some constraints such as precedence relations on the tasks, limited capacity of machines and operators, and skills of the operators to assist the processing of tasks. We analyze the problem and propose a generic schedule builder that may be adapted to build schedules in different dominant and non-dominant search spaces. The schedule builder was exploited as a …decoder in a genetic algorithm. All the proposals were evaluated on a benchmark set with instances of different characteristics. The experimental study revealed useful insights of practical interest and showed substantial improvements of the genetic algorithm over existing methods in the literature. Show more

Keywords: Scheduling, genetic algorithms, heuristics, schedule generation schemes, constraint satisfaction and optimization

DOI: 10.3233/ICA-160519

Citation: Integrated Computer-Aided Engineering, vol. 23, no. 3, pp. 269-285, 2016

Authors: Fernández-Luque, Francisco J. | Pérez, David | Zapata, Juan | Ruiz, Ramón

Article Type: Research Article

Abstract: Occupancy detection in customary resting places of people living alone at home is a main issue in Ambient Assisted Living (AAL) systems. Typical occupancy sensors are based on pressure-contact mats or load transducers with a predefined threshold which is established during the sensor installation and should be recalibrated manually if the transducer response changes. We propose an automatic calibration algorithm to get an adaptive threshold which makes the sensor robust regarding the transducer degradation, a small shift in the position of the sensor, or any other variation that modifies the characteristic response of the load sensor. An implementation of …the k-means clustering algorithm is used over a data window to get adaptive centroids that represent the values associated with each sensor state: occupied and unoccupied. The load threshold for occupancy determination is updated using these centroids. This method has demonstrated to have better percentage of success in the classification between occupancy and no occupancy (success rate) and better error margin than the fixed one. The improvement brought by the proposed adaptive method has been quantified using load data records from occupancy sensors in an AAL system deployed over 10 real homes. Success rates have been satisfactorily increased in every case, as well as error margin, which has been measured by defining a metric for the mean of the deviation of the threshold from the center of the local data. The success rate has been increased from 77.7% to 96% in the best case and from 93% to 98.6% in mean. The deviation of the threshold from the center of the local data, as an inverse measurement of the error margin, has been improved from 24.4% to 0.75% in the best case and from 9.5% to 1.14% in mean. Show more

Keywords: Adaptive thresholding, ambient assisted living, k-means, occupancy sensor, wireless sensor network

DOI: 10.3233/ICA-160521

Citation: Integrated Computer-Aided Engineering, vol. 23, no. 3, pp. 287-298, 2016

Authors: Lacabex, Borja | Cuesta-Infante, Alfredo | Montemayor, Antonio S. | Pantrigo, Juan J.

Article Type: Research Article

Abstract: In this work we present a tracking-by-detection system that works under two hard computational constraints: no parallelization and real-time performance. To this aim, we develop a lightweight method for object detection based on background subtraction, window masking and image density projections. The association of detections and trackers is carried out with the Hungarian algorithm on a loss matrix that is constructed according to position, size and appearance. In addition we include heuristics for detecting forming groups as well as incoming and outgoing pedestrians. Finally tracking is performed with particle filters. We test our system on different well-known benchmark datasets. Experimental …results reveal that the proposed method is efficient and effective. Specifically, it obtains a processing rate of up to 22 frames per second on average when tracking up to 9 people. Show more

Keywords: People detection, people tracking, tracking-by-detection, association algorithms, particle filters

DOI: 10.3233/ICA-160523

Citation: Integrated Computer-Aided Engineering, vol. 23, no. 3, pp. 299-311, 2016