SLS 2020 workshop

Held in conjunction with PPSN 2020

A workshop to be held in conjunction with the 16th International Conference on Parallel Problem Solving from Nature (PPSN 2020

Workshop Description

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.

In recent years, it has become evident that the development of effective SLS algorithms is a complex engineering process that typically combines aspects of algorithm design and implementation with empirical analysis and problem-specific background knowledge. The difficulty of this process is in part due to the complexity of the problems being tackled and in part due to the large number of degrees of freedom researchers and practitioners face when developing SLS algorithms.

This development process needs to be assisted by a sound methodology that adresses the issues arising in the phases of algorithm design, implementation, tuning and experimental evaluation. In addition, more research is required to understand which SLS techniques are best suited for particular problem types and to better understand the relationship between algorithm components, parameter settings, problem characteristics and performance.

The SLS 2020 workshop will give 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.

The SLS Workshop will solicit 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


Contact us:

• Holger Hoos - University of Leiden, The Netherlands -

• Laetitia Jourdan - University of Lille, France -

• Marie-Eléonore Kessaci - University of Lille, France -

• Thomas Stützle - Université Libre de Bruxelles, Belgium -

• Nadarajen Veerapen - University of Lille, France -


There are no format requirements. You can submit your ideas by simple mail, or as PDF. Please indicate the format of your suggested contribution (talk, discussion, breakout, brainstorming, etc.) and how much time you suggest for this activity. The workshop is also a perfect venue to share your recently published work.

Please note that PPSN workshop papers are not published in the conference proceedings.

If you do not care about being listed in the conference proceedings, you can send us your ideas/contributions/position papers/suggested activities/... any time, ideally before July 14, 2020.

Please send your suggestions for presentations and/or discussions by e-mail to