Evolutionary Computation in Combinatorial Optimization

Metaheuristicscontinuetodemonstratetheire?ectivenessforanever-broadening range of di?cult combinatorial optimization problems appearing in a wide - riety of industrial, economic, and scienti?c domains. Prominent examples of metaheuristics are evolutionary algorithms, tabu search, simulated annealing, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, ant colony optimization and estimation of distribution algorithms. Problems solved successfully include scheduling,timetabling,networkdesign,transportationanddistribution,vehicle routing, the travelling salesman problem, packing and cutting, satis?ability and general mixed integer programming. EvoCOP began in 2001 and has been held annually since then. It is the ?rst event speci?cally dedicated to the application of evolutionary computation and related methods to combinatorial optimization problems. Originally held as a workshop,EvoCOPbecameaconferencein2004.Theeventsgaveresearchersan excellent opportunity to present their latest research and to discuss current - velopments and applications.Following the general trend of hybrid metaheur- tics and diminishing boundaries between the di?erent classes of metaheuristics, EvoCOPhas broadenedits scope in recent years and invited submissions on any kind of metaheuristic for combinatorial optimization.