Call for papers

Stochastic local search (SLS) algorithms are among the most powerful techniques for solving computationally hard problems in many areas of computer science, operational research and engineering. SLS techniques range from rather simple constructive and iterative improvement algorithms to general-purpose methods, also widely known as metaheuristics, such as ant colony optimisation, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search and variable neighbourhood search.

Relevant Research Areas

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SLS 2019 is a 2-day workshop that gives researchers interested in the principles and practice of the design, implementation and analysis of stochastic local search algorithms, with a focus on automated algorithm design and analysis approaches, the opportunity to meet, to present their latest research, and to discuss current developments and applications.

SLS 2019 solicits contributions dealing with any aspect of engineering stochastic local search algorithms. Typical, but not exclusive, topics of interest are:

- New algorithmic developments
- Automated design of SLS algorithms
- In-depth experimental studies of SLS algorithms
- Theoretical analysis of SLS behaviour and their impact on the design
- Extensions to multi-objective optimisation
- Applications of SLS algorithms to real-world problems

Submission
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2-page abstract

Please note that the workshop is free of charge, but registration is mandatory to help with organisation.