Selective crossover in genetic algorithms

This paper proposes a recombination operator, “selective crossover” for use in genetic algorithm

Genetic Programming with Gene Dominance

This paper proposes the use of haploid gene dominance in genetic programming

Pharmacological Properties and Physiological Function of a P2X-Like Current in Single Proximal Tubule Cells Isolated from Frog Kidney

Although previous studies have provided evidence for the expression of P2X receptors in renal proximal tubule, only one cell line study has provided functional evidence. The current study investigated the pharmacological properties and physiological role of native P2X-like currents in single frog proximal tubule cells using the whole-cell patch-clamp technique. Extracellular ATP activated a cation conductance (P2Xf) that was also Ca2+-permeable. The agonist sequence for activation was ATP = αβ-MeATP > BzATP = 2-MeSATP, and P2Xf was inhibited by suramin, PPADS and TNP-ATP. Activation of P2Xf attenuated the rundown of a quinidine-sensitive K+ conductance, suggesting that P2Xf plays a role in K+ channel regulation. In addition, ATP/ADP apyrase and inhibitors of P2Xf inhibited regulatory volume decrease (RVD). These data are consistent with the presence of a P2X receptor that plays a role in the regulation of cell volume and K+ channels in frog renal proximal tubule cells

Royal Road Encodings and Schema Propagation in Selective Crossover

Recombination operators with high positional bias are less disruptive against adjacent genes. Therefore, it is ideal for the encoding to position epistatic genes adjacent to each other and aid GA search through genetic linkage. To produce an encoding that facilitates genetic linkage is problematic. This study focuses on selective crossover, which is an adaptive recombination operator. We propose three alternative encodings for the Royal Road problem. We use these encodings to analyse the performance of selective crossover with respect to different encodings. This study shows that the performance of selective crossover is consistent and is not affected by alternative encodings of a problem, unlike two-point crossover. The encodings are also used to understand the behaviour of selective crossover in terms of schema propagation. Experimental results indicate that selective crossover provides a better balance between exploration and exploitation than conventional recombination operators. ..

Combining ability analysis for yield related traits in F2 generation of sesame (Sesamum indicum L.)

An attempt was made to study the general and specific combining ability in sesame through 6 x 6 diallel analysis for yield and yield contributing characters viz., days to 50 % flowering, days to maturity, plant height, height to first capsule, number of branches per plant, number of internodes per plant, length of capsule, width of capsule, number of capsules per plant, number of capsules per leaf axil, number of seeds per capsule, 1000-seed weight, oil content and seed yield per plant. The analysis of variance for combining ability revealed that the mean squares due to GCA were higher than the corresponding mean squares due to SCA for days to 50 % flowering, plant height, height to first capsule, number of branches per plant, number of internodes per plant, number of capsules per leaf axil and oil content indicating the predominance of the additive type of gene action in the inheritance of these characters. Based on general combining ability, the parents G.Til-1, Borda-1, G.Til-2 and G.Til-10 were good general combiners for seed yield per plant, plant height, number of branches per plant, number of internodes per plant, length of capsule, number of capsules per plant and number of seeds per capsule. Borda-1 x G.Til-10, Kalyanpur-2 x Borda-1, G.Til-1 x Borda-1 and G.Til-2 x China were best specific combiners for seed yield and its components

Symbiotic Combination as an Alternative to Sexual Recombination in Genetic Algorithms

. Recombination in the Genetic Algorithm (GA) is supposed to enable the component characteristics from two parents to be extracted and then reassembled in different combinations -- hopefully producing an offspring that has the good characteristics of both parents. However, this can only work if it is possible to identify which parts of each parent should be extracted. Crossover in the standard GA takes subsets of genes that are adjacent on the genome. Other variations of the GA propose more sophisticated methods for identifying good subsets of genes within an individual. Our approach is different; rather than devising methods to enable successful extraction of gene-subsets from parents, we utilize variable-size individuals which represent subsets of genes from the outset. Joining together two individuals, creating an `offspring' that is twice the size, straight-forwardly produces the sum of the parents' characteristics. This form of component assembly is more closely analogo..