Crossover and Diversity: A Study about GVR
Authors
Abstract
Genetic Vehicle Representation (GVR) is atwo level representational scheme, designed
to deal in an e®ective way with all the in-
formation needed by candidate solutions, for
the Vehicle Routing Problem (VRP). In this
paper, we present an analysis on the in°u-
ence of two crossover operators in the algo-
rithm performance. A ¯rst study on diver-
sity is also presented, regarding the issues
of diversity measurement and possible rela-
tions to the algorithm performance. Results
show that for GVR one type of crossover is
more suited for solving VRP instances, and
both operators may not avoid the loss of di-
versity. Nevertheless, solutions discovered by
GVR are competitive and are the best ones
found by an evolutionary algorithm.
Keywords
Representations, Diversity, Crossover, Vehicle Routing ProblemSubject
Evolutionary OptimizationConference
a bird-of-a-feather workshop at the 2003 Genetic and Evolutionary Computation Conference (GECCO-2003), July 2003Cited by
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