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Publicações

Publicações por Jorge Valente

2017

What catches the eye in class observation? Observers' perspectives in a multidisciplinary peer observation of teaching program

Autores
Torres, AC; Lopes, A; Valente, JMS; Mouraz, A;

Publicação
TEACHING IN HIGHER EDUCATION

Abstract
Peer Observation of Teaching has raised a lot of interest as a device for quality enhancement of teaching. While much research has focused on its models, implementation schemes and feedback to the observed, little attention has been paid to what the observer actually sees and can learn from the observation. A multidisciplinary peer observation of teaching program is described, and its data is used to identify the pedagogical aspects to which lecturers pay more attention to when observing classes. The discussion addresses the valuable learning opportunities for observers provided by this program, as well as its usefulness in disseminating, sharing and clarifying quality teaching practices. The need for further research concerning teacher-student relationships and students' engagement is also suggested.

2013

A comparison of metaheuristic procedures to schedule jobs in a permutation flow shop to minimise total earliness and tardiness

Autores
Schaller, J; Valente, JMS;

Publicação
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

Abstract
This paper considers the problem of scheduling jobs in a permutation flow shop with the objective of minimising total earliness and tardiness. A genetic algorithm is proposed for the problem. This procedure and five other procedures were tested on problem sets that varied in terms of number of jobs, machines and the tightness and range of due dates. It was found that the genetic algorithm procedure was consistently effective in generating good solutions relative to the other procedures.

2016

Metaheuristics for the single machine weighted quadratic tardiness scheduling problem

Autores
Goncalves, TC; Valente, JMS; Schaller, JE;

Publicação
COMPUTERS & OPERATIONS RESEARCH

Abstract
This paper considers the single machine scheduling problem with weighted quadratic tardiness costs. Three metaheuristics are presented, namely iterated local search, variable greedy and steady-state genetic algorithm procedures. These address a gap in the existing literature, which includes branch-and-bound algorithms (which can provide optimal solutions for small problems only) and dispatching rules (which are efficient and capable of providing adequate solutions for even quite large instances). A simple local search procedure which incorporates problem specific information is also proposed. The computational results show that the proposed metaheuristics clearly outperform the best of the existing procedures. Also, they provide an optimal solution for all (or nearly all, in the case of the variable greedy heuristic) the smaller size problems. The metaheuristics are quite close in what regards solution quality. Nevertheless, the iterated local search method provides the best solution, though at the expense of additional computational time. The exact opposite is true for the variable greedy procedure, while the genetic algorithm is a good all-around performer.

2018

Iterated-greedy-based algorithms with beam search initialization for the permutation flowshop to minimise total tardiness

Autores
Fernandez Viagas, V; Valente, JMS; Framinan, JM;

Publicação
EXPERT SYSTEMS WITH APPLICATIONS

Abstract
The permutation flow shop scheduling problem is one of the most studied operations research related problems. Literally, hundreds of exact and approximate algorithms have been proposed to optimise several objective functions. In this paper we address the total tardiness criterion, which is aimed towards the satisfaction of customers in a make-to-order scenario. Although several approximate algorithms have been proposed for this problem in the literature, recent contributions for related problems suggest that there is room for improving the current available algorithms. Thus, our contribution is twofold: First, we propose a fast beam-search-based constructive heuristic that estimates the quality of partial sequences without a complete evaluation of their objective function. Second, using this constructive heuristic as initial solution, eight variations of an iterated-greedy-based algorithm are proposed. A comprehensive computational evaluation is performed to establish the efficiency of our proposals against the existing heuristics and metaheuristics for the problem.

2013

An evaluation of heuristics for scheduling a non-delay permutation flow shop with family setups to minimize total earliness and tardiness

Autores
Schaller, J; Valente, JMS;

Publicação
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY

Abstract
This paper presents several procedures for developing non-delay schedules for a permutation flow shop with family setups when the objective is to minimize total earliness and tardiness. These procedures consist of heuristics that were found to be effective for minimizing total tardiness in flow shops without family setups, modified to consider family setups and the total earliness and tardiness objective. These procedures are tested on several problem sets with varying conditions. The results show that variable greedy algorithms are effective when solving small problems, but using a genetic algorithm that includes a neighbourhood defined by the sequence of batches of jobs belonging to the same set-up family is effective when solving medium- or large-sized problems. The results also show that if setup times can be reduced a significant reduction in total earliness and tardiness could result.

2018

Efficient heuristics for minimizing weighted sum of squared tardiness on identical parallel machines

Autores
Schaller, J; Valente, JMS;

Publicação
COMPUTERS & INDUSTRIAL ENGINEERING

Abstract
Scheduling jobs on a set of identical parallel machines using efficient heuristics when the objective is to minimize total weighted squared tardiness is considered. Two efficient heuristics and an improvement procedure are presented for the problem. These heuristics and other heuristics are tested using problem sets that represent a variety of conditions. The results show that one of the heuristics consistently performs better than the other heuristics tested. It is also shown how these heuristics can be incorporated into other procedures such as the existing Lagrangian relaxation procedure or meta-heuristics to obtain improved solutions for medium sized problems.

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