Permutation-based optimization problems are a class of combinatorial optimization problems that naturally arises in many real world applications and theoretical scenarios where an optimal ordering or ranking of items has to be found with respect to one or more objective criteria. Some popular examples are: flowshop scheduling problem, traveling salesman problem, quadratic assignment problem and linear ordering problem.

Since the first paper on the traveling salesman problem in 1985 by Goldberg, permutation problems have been recurrently addressed in the field of Evolutionary Computation (EC) from a wide variety of perspectives. Evolutionary algorithms, fitness landscape analysis, genotypic representations or probabilistic modeling on rankings are only a few of the topics that have been discussed in the literature.

In modern combinatorics, permutations are probably among the richest combinatorial structures. Motivated principally by their versatility - ordered set of items, collection of disjoint cycles, transpositions, matrices or graphs - permutations appear in a vast range of domains, thus making permutation problems a very special case where ideas and concepts originated from classical mathematic fields, such as algebra, geometry, and probability theory, can be exploited and used in the design of new metaheuristics and genetic operators.

All these aspects have recently motivated a strong and ongoing research interest towards permutation problems in EC. Therefore, this workshop aims to highlight the most recent advances in the field and to bring together the EC researchers working in all the aspects of permutation problems.

Authors are invited to submit their original and unpublished work in the areas including, but not limited to:

- EC applications to the flowshop scheduling problem
- EC applications to the traveling salesman problem
- EC applications to the linear ordering problem
- EC applications to the quadratic assignment problem
- EC applications to any kind of single or multiple objective(s) permutation-based optimization problem
- Novel permutation-based optimization problems in EC
- Fitness landscape analysis of permutation-based optimization problems
- Theoretical analysis of permutation search spaces, meta-heuristics and hardness of problem instances
- Algebraic models for EC in permutation-based search spaces
- Probabilistic models for EC in permutation-based search spaces
- Permutation genotypic representations for EC techniques
- Experimental evaluations and comparisons of EC techniques for permutation-based optimization problems