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Fitness landscape analysis techniques are used to better understand the influence of genetic representations and associated variation operators when solving a combinatorial optimization problem. Five representations are investigated for the multidimensional knapsack problem. Common mutation operators, such as bit-flip mutation, are employed to generate(More)
In this paper we analyse a new evolutionary approach to the vehicle routing problem. We present Genetic Vehicle Representation (GVR), a two-level representational scheme designed to deal in an effective way with all the information that candidate solutions must encode. Experimental results show that this method is both effective and robust, allowing the(More)
In this paper we discuss the evolution of several components of a traditional Evolutionary Algorithm, such as genotype to phenotype mappings and genetic operators, presenting a formalized description of how this can be attained. We then focus on the evolution of mapping functions, for which we present experimental results achieved with a meta-evolutionary(More)
A comparative study is made between a new evolutionary approach for the Vehicle Routing Problem (VRP) and a standard evolutionary model, based on Path Representation. Genetic Vehicle Representation (GVR) is the new two-level representational scheme designed to deal in an effective way with all the information needed by candidate solutions. Experimental(More)
This paper proposes a Grammatical Evolution framework to the automatic design of Evolutionary Algorithms. We define a grammar that has the ability to combine components regularly appearing in existing evolutionary algorithms, aiming to achieve novel and fully functional optimization methods. The problem of the Royal Road Functions is used to assess the(More)
The success of the application of evolutionary approaches depends, to a large extent, on problem representation and on the used genetic operators. In this paper we introduce a new graph based crossover operator and compare it with classical two-point crossover. The study was carried out using a theoretical hard problem known as Busy Beaver. This problem(More)
In this paper we describe three evolutionary approaches to the vehicle routing problem. In our first approach we use a standard genetic algorithm whilst in the second we use a coevolutionary model. The third approach concerns the extension of the previous ones through the inclusion of heuristics. We present and compare the experimental results achieved by(More)