Fernando Melicio

High school weekly timetabling by evolutionary algorithms

This paper describes a method for generating high school timetables using an Evolutionary Algorithm (E.A.). Given c classes. t teachers and r classrooms it is required to build a set of c+t+r timetables based on the needs of the school and satisfying constraints in the assignment of the lessons. A problem specific chromosome representation and the use of a repair function during titness evaluation helps the algorithm, keeping the search close to valid solutions. Our new operator, ‘Bad Genes Mutation’, greatly improved the algorithm’s speed and results. Test results on a large high school are presented. 1 THE SCHOOL TlMETABLlNG PROBLEM In this section we describe in detail the schooltimetabling problem and discuss the hard and soft [Z] constraints considered in the assignment of a lesson. 1.7 Defining the Problem Conditions We define time slot duration as the greatest common factor of all the different lesson durations i.e. if we only have sixty-minute and ninety-minute lessons then the time slot duration will be th’irty minutes. We define the dimension (number of timeslots) of each timetable as: dimension = rrulnber-of-days-wit/l-lessons * number-hne_slotsJerJay The most common division of timetables into time slots used in schools is a sixty-minute time slot. ten times a day and five days a week, as shown in Figure 1. p-ission ~0 m&e di&al or hard copies Of dt Oc @ Oftis wk for p-d 0~ classroom use is pnttd without fee pm”ia thJ copime no( made OT distributed fOr FOffi 01 COll’UnS~

Using a hybrid Evolutionary-Taboo Algorithm to solve Job Shop Problem

&an(a8e and that copies bear this notice and the full citation on he first page. To copy otherwise, to republish to P.04 on Seem 0~ to redi&bute to lists, requires prior Specific pennlmm a&of a fee. SAC 99, San Antonio, Texas 61998 ACM l-58113-0864991ooO1 S5.00 Fernando Melicio’ Agostinho Rosa I.S.E.L. LaSEEB-ISR-IST R. Conselheiro Emidio Navarro Av. Rovisco Pais, I. TN 6.21 1900 Lisboa I O49IO0 Lisboa Codex Portugal Portugal Fmelicio@isel.ot Acrosa@isr.ist.utl.ot Fig I Map for the assipnent t,f the lesssscms. Each time SIOI is asswiuted with a number

In-Plane Displacement and Strain Image Analysis

In this paper, we propose a new hybrid algorithm to solve the Job Shop Problem. Our algorithm, called Evoluntionary-Taboo uses an Evolutionary Algorithm (EA) to enhance results obtained by one of the best Taboo algorithms for this problem. We tested the algorithm on the benchmark problems for which the taboo algorithm returned its worst results. On average, we improved taboo results by 2.9%. The results were under one percent from the best known results for these problems.

Object recognition test in peripheral vision: a study on the influence of object color, pattern and shape

Measurements in civil engineering load tests usually require considerable time and complex procedures. Therefore, measurements are usually constrained by the number of sensors resulting in a restricted monitored area. Image processing analysis is an alternative way that enables the measurement of the complete area of interest with a simple and effective setup. In this article photo sequences taken during load displacement tests were captured by a digital camera and processed with image correlation algorithms. Three different image processing algorithms were used with real images taken from tests using specimens of PVC and Plexiglas. The data obtained from the image processing algorithms were also compared with the data from physical sensors. A complete displacement and strain map were obtained. Results show that the accuracy of the measurements obtained by photogrammetry is equivalent to that from the physical sensors but with much less equipment and fewer setup requirements.

A Shuffled Complex Evolution Based Algorithm for Examination Timetabling - Benchmarks and a New Problem Focusing Two Epochs

As an important factor for central vision preview, peripheral vision is a crucial ability for most ball game players in motion detection. A critical problem with peripheral vision is object recognition which has not yet been given much attention. This paper presents an experimental study to evaluate the influence on object recognition in peripheral vision due to different patterns, colors and shapes of the objects. More specifically, four types of shapes (including circles, triangles, horizontal stripes and vertical stripes) with various colors presented in different patterns were applied during the peripheral vision test. The results show that different patterns and colors indeed affect object recognition in peripheral vision in terms of accuracy and response time, while different types of shapes do not vary the performance significantly.

Dynamic peripheral visual performance relates to alpha activity in soccer players

In this work we present a memetic algorithm for solving examination timetabling problems. Two problems are analysed and solved. The first one is the well-studied single-epoch problem. The second problem studied is an extension of the standard problem where two examination epochs are considered, with different durations. The proposed memetic algorithm inherits the population structure of the Shuffled Complex Evolution algorithm, where the population is organized into sets called complexes. These complexes are evolved independently and then shuffled in order to generate the next generation complexes. In order to explore new solutions, a crossover between two complex’s solutions is done. Then, a random solution selected from the top best solutions is improved, by applying a local search step where the Great Deluge algorithm is employed. Experimental evaluation was carried out on the public uncapacitated Toronto benchmarks (single epoch) and on the ISEL-DEETC department examination benchmark (two epochs). Experimental results show that the proposed algorithm is efficient and competitive on the Toronto benchmarks with other algorithms from the literature. Relating the ISEL-DEETC benchmark, the algorithm attains a lower cost when compared with the manual solution.

Multimodal semantic characterization of images using MPEG-7 descriptors

Many studies have demonstrated the relationship between the alpha activity and the central visual ability, in which the visual ability is usually assessed through static stimuli. Besides static circumstance, however in the real environment there are often dynamic changes and the peripheral visual ability in a dynamic environment (i.e., dynamic peripheral visual ability) is important for all people. So far, no work has reported whether there is a relationship between the dynamic peripheral visual ability and the alpha activity. Thus, the objective of this study was to investigate their relationship. Sixty-two soccer players performed a newly designed peripheral vision task in which the visual stimuli were dynamic, while their EEG signals were recorded from Cz, O1, and O2 locations. The relationship between the dynamic peripheral visual performance and the alpha activity was examined by the percentage-bend correlation test. The results indicated no significant correlation between the dynamic peripheral visual performance and the alpha amplitudes in the eyes-open and eyes-closed resting condition. However, it was not the case for the alpha activity during the peripheral vision task: the dynamic peripheral visual performance showed significant positive inter-individual correlations with the amplitudes in the alpha band (8–12 Hz) and the individual alpha band (IAB) during the peripheral vision task. A potential application of this finding is to improve the dynamic peripheral visual performance by up-regulating alpha activity using neuromodulation techniques.

A Hybrid Shuffled Frog-Leaping Algorithm for the University Examination Timetabling Problem

In this paper the edge histogram descriptor, the scalable colour descriptor and the colour layout descriptor defined in the MPEG-7 standard are used for image semantic characterization. A comparative study of the performance and reliability of the image classification based in these descriptors is made. For that, classification methods like neural networks and k-nearest neighbors were used to detect relevant semantic features in images. The descriptors are individually used and combined with different multimodal techniques. A set with 460 images will be used for testing together with a set of 320 training images selected from the TRECVID 2008 development sound and vision database was used.

Solving a Capacitated Exam Timetabling Problem Instance Using a Bi-objective NSGA-II

The problem of examination timetabling is studied in this work. We propose a hybrid solution heuristic based on the Shuffled Frog-Leaping Algorithm (SFLA) for minimising the conflicts in the students’s exams. The hybrid algorithm, named Hybrid SFLA (HSFLA), improves a population of frogs (solutions) by iteratively optimising each memeplex, and then shuffling the memeplexes in order to distribute the best performing frogs by the memeplexes. In each iteration the frogs are improved based on three operators: crossover and mutation operators, and a local search operator based on the Simulated Annealing metaheuristic. For the mutation and local search, we use two well known neighbourhood structures. The performance of the proposed method is evaluated on the 13 instances of the Toronto datasets from the literature. Computational results show that the HSFLA is competitive with state-of-the-art methods, obtaining the best results on average in seven of the 13 instances.

Displacement Measurements with ARPS in T-Beams Load Tests

This paper describes a hybrid bi-objective evolutionary algorithm, based on the Non-dominated Sorting Genetic Algorithm-II (or NSGA-II) for solving the Capacitated University Examination Timetable Problem. The instance solved is the timetable of the Electrical, Telecommunications and Computer Engineering Department at the Lisbon Polytechnic Institute, which comprises three bachelor programs and two master programs, having about 80 courses offered and 1200 students enrolled. The examination timetable build in a manual form takes about one week long, considering a two-person team. The proposed bi-objective algorithm incorporates the following objectives: (1) minimization of the number of occurrences of students having to take exams in consecutive days, and (2) the minimization of the timetable length. The computational results show that the automatic algorithm achieves better results compared to the manual solution, and in negligible time. After the optimization of each non-dominated feasible timetable, a room allocation procedure is used to allocate exams rooms.