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About

Hello!

I am a teacher at the Faculty of Economics, University of Porto, and a researcher at LIAAD, one of INESC TEC's  research groups.

My research mostly involves the development and application of (meta)heuristic procedures to combinatorial optimization problems, particularly scheduling problems. Currently, I am also learning data mining.

Interest
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Details

Details

  • Name

    Jorge Valente
  • Cluster

    Computer Science
  • Role

    Research Coordinator
  • Since

    01st October 2012
Publications

2022

Metaheuristics for the permutation flowshop problem with a weighted quadratic tardiness objective

Authors
Silva, AF; Valente, JMS; Schaller, JE;

Publication
COMPUTERS & OPERATIONS RESEARCH

Abstract
In this paper, we consider a permutation flowshop problem, with a weighted squared tardiness objective function, which addresses an important criterion for many customers. Our objective is to find metaheuristics that can, within acceptable computational times, provide sizeable improvements in solution quality over the best existing procedure (a dispatching rule followed by an improvement method). We consider four metaheuristics, namely iterated local search (ILS), iterated greedy (IG), variable greedy (VG) and steady-state genetic algorithms (SSGA). These are known for performing well on permutation flowshops and/or on tardiness criteria. For each metaheuristic, four versions are developed, differing on the choice of initial sequence and/or local search. Additionally, four different time limits are considered. Therefore, a total of 64 sets of results are obtained. The results show that all procedures greatly outperform the best existing method. The IG procedures provide the best results, followed by the SSGA procedures. The VG methods are usually inferior to SSGA, while the ILS metaheuristics tend to be the worst performers. The four metaheuristics prove to be robust in what regards initial solution and local search method, since both have little effect on the performance of the metaheuristics. Increasing the time limit does improve the performance of all procedures. Still, a sizeable improvement is obtained even for the lowest time limit. Therefore, even under restrictive time limits, the metaheuristics greatly outperform the best existing procedure.

2020

Minimizing total earliness and tardiness in a nowait flow shop

Authors
Schaller, J; Valente, JMS;

Publication
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS

Abstract
This paper considers the problem of scheduling jobs in a no-wait flow shop with the objective of minimizing total earliness and tardiness. An exact branch-and-bound algorithm is developed for the problem. Several dispatching heuristics used previously for other environments and two new heuristics were tested under a variety of conditions. It was found that one of the new heuristics consistently performed well compared to the others. An insertion search improvement procedure with speed up methods based on the structure of the problem was proposed and was found to deliver much improved solutions in a reasonable amount of time.

2020

Efficient procedures for the weighted squared tardiness permutation flowshop scheduling problem

Authors
Costa, MRC; Valente, JMS; Schaller, JE;

Publication
FLEXIBLE SERVICES AND MANUFACTURING JOURNAL

Abstract
This paper addresses a permutation flowshop scheduling problem, with the objective of minimizing total weighted squared tardiness. The focus is on providing efficient procedures that can quickly solve medium or even large instances. Within this context, we first present multiple dispatching heuristics. These include general rules suited to various due date-related environments, heuristics developed for the problem with a linear objective function, and procedures that are suitably adapted to take the squared objective into account. Then, we describe several improvement procedures, which use one or more of three techniques. These procedures are used to improve the solution obtained by the best dispatching rule. Computational results show that the quadratic rules greatly outperform the linear counterparts, and that one of the quadratic rules is the overall best performing dispatching heuristic. The computational tests also show that all procedures significantly improve upon the initial solution. The non-dominated procedures, when considering both solution quality and runtime, are identified. The best dispatching rule, and two of the non-dominated improvement procedures, are quite efficient, and can be applied to even very large-sized problems. The remaining non-dominated improvement method can provide somewhat higher quality solutions, but it may need excessive time for extremely large instances.

2019

Heuristics for scheduling jobs in a permutation flow shop to minimize total earliness and tardiness with unforced idle time allowed

Authors
Schaller, J; Valente, JMS;

Publication
EXPERT SYSTEMS WITH APPLICATIONS

Abstract
This paper considers the problem of scheduling jobs in a permutation flow shop with the objective of minimizing total earliness and tardiness. Unforced idle time is considered in order to reduce the earliness of jobs. It is shown how unforced idle time can be inserted on the final machine. Several dispatching heuristics that have been used for the problem without unforced idle time were modified and tested. Several procedures were also developed that conduct a second pass to develop a sequence using dispatching rules. These procedures were also tested and were found to result in better solutions.

2019

Branch-and-bound algorithms for minimizing total earliness and tardiness in a two-machine permutation flow shop with unforced idle allowed

Authors
Schaller, J; Valente, J;

Publication
COMPUTERS & OPERATIONS RESEARCH

Abstract
The two-machine permutation flow shop scheduling problem with the objective of minimizing total earliness and tardiness is addressed. Unforced idle time can be used to complete jobs closer to their due dates. It is shown that unforced idle time only needs to be considered on the second machine. This result is then used to extend a lower bound and dominance conditions for the single-machine problem to the two-machine permutation flow shop problem. Two branch-and-bound algorithms are developed for the problem utilizing the lower bound and dominance conditions. The algorithms are tested using instances that represent a wide variety of conditions.

Supervised
thesis

2021

A real-time decision support system for guiding logistics vehicle operations

Author
Sara Cláudio

Institution
UP-FEP

2021

Space elasticities analysis in food retail: application to a Portuguese retailer

Author
Diana Raquel Ferreira Ribeiro

Institution
UP-FEP

2020

Marketplace Landing Page Optimization on Fashion Retail

Author
Raquel Alexandra Gonçalves Peixoto

Institution
UP-FEP

2019

Heuristics for the Distributed Permutation Flowshop Scheduling Problem with the Weighted Tardiness Objective

Author
Maria Inês Ferraz Cerveira

Institution
UP-FEP

2018

Adaptive learning redemption rate prediction model

Author
Camila Helena Ölund Matos

Institution
UP-FEP