The 20th European Conference on Evolutionary Computation in Combinatorial Optimisation

EvoCop 2020


Evolutionary Computation



The 20th European Conference on Evolutionary Computation in Combinatorial Optimisation is a multidisciplinary conference that brings together researchers working on evolutionary computation methods and other metaheuristics for solving difficult combinatorial optimisation problems appearing in various industrial, economic, and scientific domains. Prominent examples of metaheuristics include: evolutionary algorithms, estimation of distribution algorithms, swarm intelligence methods such as ant colony and particle swarm optimisation, local search methods such as simulated annealing, tabu search, variable neighbourhood search, iterated local search, scatter search and path relinking, and their hybridisation, such as memetic algorithms. Automatic algorithm configuration and design, meta-optimisation, model-based methods, and hyperheuristics are also topics of interest. Successfully solved problems include, but are not limited to, multi-objective, uncertain, dynamic and stochastic problems in the context of scheduling, timetabling, network design, transportation and distribution, vehicle routing, graph problems, satisfiability, energy optimisation, cutting, packing, and planning problems.
The EvoCOP 2020 conference will be held in the city of Seville, Spain, together with EuroGP (the 23rd European Conference on Genetic Programming), EvoMUSART (the 9th European conference on evolutionary and biologically inspired music, sound, art and design) and EvoApplications (the 23rd European Conference on the Applications of Evolutionary Computation), in a joint event collectively known as EvoStar (Evo*).
EvoCOP Conference Proceedings in SpringerLink: https://link.springer.com/conference/evocop
Areas of Interest and Contributions
Topics of interest include, but are not limited to:
Applications of metaheuristics to combinatorial optimisation problems
Representation techniques
Practical solution of NP-hard problems
Neighbourhoods and efficient algorithms for searching them
Variation operators for stochastic search methods
Theoretical developments
Constraint-handling techniques
Parallelisation and grid computing
Search space and landscape analyses
Comparisons between different (also exact) methods
Heuristics
Genetic programming and Genetic algorithms
Tabu search, iterated local search and variable neighbourhood search
Ant colony optimisation
Artificial immune systems
Scatter search
Particle swarm optimisation
Memetic algorithms
Hybrid methods and hybridisation techniques
Matheuristics (hybrids of exact and heuristic methods)
Hyper-heuristics and autonomous search
Automatic algorithm configuration and design
Metaheuristics and machine learning
Surrogate-model-based methods
Estimation of distribution algorithms
String processing
Scheduling and timetabling
Network design
Vehicle routing
Graph problems
Satisfiability
Packing and cutting problems
Energy optimisation problems
Multi-objective optimisation
Search-based software engineering
Notice that, by tradition, continuous/numerical optimisation is *not* part of the topics of interest of EvoCOP. Interested authors might consider submitting to other EvoStar conferences such as EvoApplications.