The mutation and cross-over operators are, with selection, the foundation of genetic algorithms. We show in this paper, some possibilities offered by these operators. Having explained the specificity of the most known operators (1-point, p-point and uniform cross-over, classical and deterministic mutation) we introduce new crossover and mutation operators with a low cost in term of execution ti...

This paper proposes a new type of mutation operator, FEDS (Fitness, Elitism, Depth, and Size) mutation in genetic programming. The concept behind the new mutation operator is inspired from already introduced FEDS crossover operator to handle the problem of code bloating. FEDS mutation operates by using local elitism replacement in combination with depth limit and size of the trees to reduce blo...

This paper presents a comparison in the performance analysis between a newly developed crossover operator called Rayleigh Crossover (RX) and an existing crossover operator called Laplace Crossover (LX). Coherent to the previously defined Scaled Truncated Pareto Mutation (STPM) operator to form two (2) generational RCGAs called RX-STPM and LX-STPM, both crossovers are utilized. A set of ten (10)...

The dynamic behavior of mutation and crossover is investigated with the Breeder Genetic Algorithm. The main emphasis is on binary functions. The genetic operators are compared near their optimal performance. It is shown that mutation is most eecient in small populations. Crossover critically depends on the size of the population. Mutation is the more robust search operator. But the BGA combines...

The dynamic behavior of mutation and crossover is investigated with the Breeder Genetic Algorithm The main emphasis is on binary functions The genetic operators are compared near their optimal performance It is shown that mutation is most e cient in small populations Crossover critically depends on the size of the population Mutation is the more robust search operator But the BGA combines the t...

Bridges constitute an expensive segment of construction projects; the optimization of their designs will affect their high cost. Segmental precast concrete bridges are one of the most commonly serviced bridges built for mid and long spans. Genetic algorithm is one of the most widely applied meta-heuristic algorithms due to its ability in optimizing cost. Next to providing cost optimization of t...

Hubs are centers for collection, rearrangement, and redistribution of commodities in transportation networks. In this paper, non-linear multi-objective formulations for single and multiple allocation hub maximal covering problems as well as the linearized versions are proposed. The formulations substantially mitigate complexity of the existing models due to the fewer number of constraints and v...

This work analyzes fitness landscapes for the image filter design problem approached using functional-level Cartesian Genetic Programming. Smoothness and ruggedness of fitness landscapes are investigated for five genetic operators. It is shown that the mutation operator and the single-point crossover operator generate the smoothest landscapes and thus they are useful for practical applications ...

Differential evolution (DE) is an efficient and robust evolutionary algorithm and has wide application in various science and engineering fields. DE is sensitive to the selection of mutation and crossover strategies and their associated control parameters. However, the structure and implementation of DEs are becoming more complex because of the diverse mutation and crossover strategies that use...