Propostas atribuídas ano letico 2025/2026

DEI - FCTUC
Gerado a 2025-08-31 18:11:33 (Europe/Lisbon).
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Titulo Estágio

Compression Techniques for Optimization Algorithms

Área Tecnológica

Sistemas Evol. e Comp.

Local do Estágio

ECOS/CISUC

Enquadramento

Many algorithms for optimization have to maintain a large pool of potential solutions to a given problem, such as evolutionary algorithms, or algorithms for multicriteria optimization. In order to run these algorithms in devices with few memory available, special algorithms and data structures are needed to compress and uncompress solutions in an efficient manner, without bringing too much computational cost (see . G. R. Raidl and B. Hu., Enhancing genetic algorithms by a trie-based complete solution archive., In P. Cowling and P. Merz, editors, Evolutionary Computation in Combinatorial Optimisation - EvoCOP 2010, volume 6022 of LNCS, pages 239-251. Springer, 2010). Several compression techniques are available but they have been used quite rarely in the context of algorithms for optimization.

Objetivo

The goal is to design and analyse algorithms and data structures that compress and uncompress solutions for a given set of real-life optimization problems, such as the knapsack problem, the shortest path problem and sequence alignment problem. The solutions to these problems are usually represented as a sequence of strings or integers as well as permutations and graphs. The student will consider compression techniques at run-lenght enconding level (e.g., Lempel-Ziv technique) and at data-structure level (e.g. tries and directed acyclic word graphs). The final goal is to perform an in-depth experimental analysis that allows to understand the trade-off memory vs. time of compression techniques in optimization algorithms.

Plano de Trabalhos - Semestre 1

1 Month: Problem identification
2 Months: Literature review on compression techniques and optimization algorithms
1 Month: Writing of the preliminary report (includes a description of the main compression techniques and their application to optimization algorithms).

Plano de Trabalhos - Semestre 2

2 Months: Algorithm implementation 
1 Month: Experimental analysis
1 Month: Thesis writing.

Condições

The ECOSLab and its computing resources are available for performing
experiments. The research group owns a computer cluster for the
experimental analysis.

Observações

The student will work in a very motivated research group with wide international visibility. He/she will strengthen his abilities on the design and analysis of algorithms and data structures for problem solving and will develop advanced programming skills. This type of work is appropriate to students that want to follow an academic career in design and analysis of algorithms.

Students with excellent record on Algorithms and Data Structures, Advanced Programming Lab and Evolutionary Computation are highly preferable. Good experience in C, C++, or Java is also necessary.

Orientador

Luis Paquete
paquete@dei.uc.pt 📩