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Evolutionary Computation in Combinatorial Optimization

15th European Conference, EvoCOP 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings

This book constitutes the refereed proceedings of the 15th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2015, held in Copenhagen, Denmark, in April 2015, co-located with the Evo*2015 events EuroGP, EvoMUSART and EvoApplications. The 19 revised full papers presented were carefully reviewed and selected from 46 submissions. The papers cover methodology, applications and theoretical studies. The methods included evolutionary and memetic (hybrid) algorithms, iterated local search, variable neighbourhood search, ant colony optimization, artificial immune systems, hyper-heuristics and other adaptive approaches. The applications include both traditional domains, such as graph coloring, knapsack, vehicle routing, job-shop scheduling, the p-median and the orienteering problems; and new(er) domains such as designing deep recurrent neural networks, detecting network community structure, lock scheduling of ships, cloud resource management, the fire-fighter problem and AI planning. The theoretical studies involved approximation ratio, runtime and black-box complexity analyses.

A Biased Random-Key Genetic Algorithm for the Cloud Resource Management
Problem Leonard Heilig1(B), Eduardo ... Flexible use options and associated
cost savings of cloud computing are increasingly attracting the interest from both
 ...

Evolutionary Computation in Combinatorial Optimization

14th European Conference, EvoCOP 2014, Granada, Spain, April 23-25, 2014, Revised Selected Papers

This book constitutes the refereed proceedings of the 14th European Conference on Evolutionary Computation in Combinatorial Optimization, Evo COP 2014, held in Granada, Spain, in April 2014, co-located with the Evo*2014 events Euro GP, Evo BIO, Evo MUSART and Evo Applications. The 20 revised full papers presented were carefully reviewed and selected from 42 submissions. The papers cover the following topics: swarm intelligence algorithms, fitness landscapes and adaptive algorithms, real world and routing problems and cooperative and metaheuristic search.

During past decades, metaheuristic algorithms have been shown to be provenly
effective for a wide range of hard combinatorial optimization problems arising in a
variety of industrial, economic, and scientific settings. Well-known exam- ples of ...