Holger Hoos, University of Leiden, The Netherlands,
Laetitia Jourdan, University of Lille, France,
Marie-Ele ́onore Kessacib, University of Lille, France
Thomas Stu ̈tzle, Universite ́ Libre de Bruxelles, Belgium
Nadarajen Veerapen, University of Lille, France

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 optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood 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 addresses 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.

This special issue of the International Transactions in Operational Research (ITOR) is devoted to recent research, current developments, and applications of Stochastic Local Search (SLS). This includes the principles and the practice of the design, implementation, and analysis of stochastic local search algorithms, with a focus on automated algorithm design and analysis approaches.

Although we strongly encourage authors who presented work in these areas at the International Workshop SLS2019 on Stochastic Local Search Algorithms (held in Lille on September 12–13, 2019, https://sls2019.sciencesconf.org) to submit their manuscripts, this Call for Papers is also open to the entire community of academics and practitioners.

Topics for this special issue include (but are not limited to):
* New algorithmic developments
* Automated design of SLS algorithms
* In-depth experimental studies of SLS algorithms
* Theoretical analysis of SLS behavior and their impact on design r Extensions to multi-objective optimization
* Applications of SLS algorithms to real-world problems

The deadline for submissions is March 16, 2020. Papers will be peer-reviewed according to the editorial policy of ITOR, published by the International Federation of Operational Research Societies (IFORS). They should be original, unpublished, and not currently under consideration for publication elsewhere. Contributions should be prepared according to the instructions to authors that can be found on the journal homepage. Authors should upload their contributions using the submission site http://mc.manuscriptcentral.com/itor, indicating in their cover letter that the paper is intended for this special issue. Other inquiries should be sent directly to the Guest Editors in charge of this issue: Holger Hoos (hh@liacs.nl), Laetitia Jourdan (laetitia.jourdan@univ-lille.fr), Marie-Ele ́ onore Kessaci (marie-eleonore.kessaci@univ-lille.fr), Thomas Stu tzle (stuetzle@ulb.ac.be), Nadarajen Veerapen (nadarajen.veerapen@univ-lille.fr).