Prescriptive formalism for constructing domain-specific evolutionary algorithms

It has been widely recognised in the computational intelligence and machine learning communities that the key to understanding the behaviour of learning algorithms is to understand what representation is employed to capture and manipulate knowledge acquired during the learning process. However, traditional evolutionary algorithms have tended to employ a fixed representation space (binary strings), in order to allow the use of standardised genetic operators. This approach leads to complications for many problem domains, as it forces a somewhat artificial mapping between the problem variables and the canonical binary representation, especially when there are dependencies between problem variables (e.g. problems naturally defined over permutations). This often obscures the relationship between genetic structure and problem features, making it difficult to understand the actions of the standard genetic operators with reference to problem-specific structures. This thesis instead advocates m..

An efficient memetic, permutation-based evolutionary algorithm for real-world train timetabling

Train timetabling is a difficult and very tightly constrained combinatorial problem that deals with the construction of train schedules. We focus on the particular problem of local reconstruction of the schedule following a small perturbation, seeking minimisation of the total accumulated delay by adapting times of departure and arrival for each train and allocation of resources (tracks, routing nodes, etc.). We describe a permutation-based evolutionary algorithm that relies on a semi-greedy heuristic to gradually reconstruct the schedule by inserting trains one after the other following the permutation. This algorithm can be hybridised with ILOG commercial MIP programming tool CPLEX in a coarse-grained manner: the evolutionary part is used to quickly obtain a good but suboptimal solution and this intermediate solution is refined using CPLEX. Experimental results are presented on a large real-world case involving more than one million variables and 2 million constraints. Results are surprisingly good as the evolutionary algorithm, alone or hybridised, produces excellent solutions much faster than CPLEX alone

On the Benefits of Inoculation, an Example in Train Scheduling

The local reconstruction of a railway schedule following a small perturbation of the traffic, seeking minimization of the total accumulated delay, is a very difficult and tightly constrained combinatorial problem. Notoriously enough, the railway company's public image degrades proportionally to the amount of daily delays, and the same goes for its profit! This paper describes an inoculation procedure which greatly enhances an evolutionary algorithm for train re-scheduling. The procedure consists in building the initial population around a pre-computed solution based on problem-related information available beforehand. The optimization is performed by adapting times of departure and arrival, as well as allocation of tracks, for each train at each station. This is achieved by a permutation-based evolutionary algorithm that relies on a semi-greedy heuristic scheduler to gradually reconstruct the schedule by inserting trains one after another. Experimental results are presented on various instances of a large real-world case involving around 500 trains and more than 1 million constraints. In terms of competition with commercial math ematical programming tool ILOG CPLEX, it appears that within a large class of instances, excluding trivial instances as well as too difficult ones, and with very few exceptions, a clever initialization turns an encouraging failure into a clear-cut success auguring of substantial financial savings

RGFGA: An efficient representation and crossover for grouping genetic algorithms

There is substantial research into genetic algorithms that are used to group large numbers of objects into mutually exclusive subsets based upon some fitness function. However, nearly all methods involve degeneracy to some degree. We introduce a new representation for grouping genetic algorithms, the restricted growth function genetic algorithm, that effectively removes all degeneracy, resulting in a more efficient search. A new crossover operator is also described that exploits a measure of similarity between chromosomes in a population. Using several synthetic datasets, we compare the performance of our representation and crossover with another well known state-of-the-art GA method, a strawman optimisation method and a well-established statistical clustering algorithm, with encouraging results

Towards an Information Theoretic Framework for Evolutionary Learning

The vital essence of evolutionary learning consists of information flows between the environment and the entities differentially surviving and reproducing therein. Gain or loss of information in individuals and populations due to evolutionary steps should be considered in evolutionary algorithm theory and practice. Information theory has rarely been applied to evolutionary computation - a lacuna that this dissertation addresses, with an emphasis on objectively and explicitly evaluating the ensemble models implicit in evolutionary learning. Information theoretic functionals can provide objective, justifiable, general, computable, commensurate measures of fitness and diversity. We identify information transmission channels implicit in evolutionary learning. We define information distance metrics and indices for ensembles. We extend Price\u27s Theorem to non-random mating, give it an effective fitness interpretation and decompose it to show the key factors influencing heritability and evolvability. We argue that heritability and evolvability of our information theoretic indicators are high. We illustrate use of our indices for reproductive and survival selection. We develop algorithms to estimate information theoretic quantities on mixed continuous and discrete data via the empirical copula and information dimension. We extend statistical resampling. We present experimental and real world application results: chaotic time series prediction; parity; complex continuous functions; industrial process control; and small sample social science data. We formalize conjectures regarding evolutionary learning and information geometry

Incidence of Fusarium Wilt of Flax Influenced by Biotic and Abiotic Factors

Pathogenicity tests of different Fusarium spp. isolated from roots of wilted flax plants and flax seeds, showed that all pathogenic isolates were F. oxysporum. The nonpathogenic Fusarium spp. included F. moniliforme, F. solani, F. oxysporum and F. acuminatym. Cross protection tests of the nonpathogenic isolates of Fusarium spp. revealed that the large majority of the isolates which had outstanding cross-protective ability were E. oxysporum, and large differences in cross-protective ability were observed. Simultaneous inoculation of seven flax cultivars with a highly virulent isolate of F. oxysportm f.sp. lini and a nonpathogenic isolate of F. oxysporuron, significantly decreased the amount of wilt of all tested cultivars. However, the cultivars varied in the magnitude of their response to the cross-protective effect conferred by the nonpathogenic isolate. Similarly, the pathogenic isolates of E. oxysporuro f.sp. lini responded differently to the cross-protective effect of a nonpathogenic isolate of E. oxysporum. In general, the highly pathogenic isolates of F. oxysporum f.sp. lini were more responsive to cross protection than weakly pathogenic ones. The interaction between pathogenic isolates of F. oxysporym f.sp. lini, flax cultivars, and temperature was investigated. The results Showed that cultivar X isolate (P ≤ 0.001), cultivar X temperature (P ≤ 0.001), and isolate X temperature (P ≤ 0.001), were all very highly significant sources of variation. The cultivar X isolate X temperature interaction (P ≤ 0.01) was a highly significant source of variation. The effect of ineculum density on cultivar resistance, isolate virulence and their interaction was studied. The results indicated that, cultivar X inoculum, isolate X inoculum and cultivar X isolate X inoculum were all nonsignificant sources of variation. Analysis of inoculum density-disease incidence (ID-DI) relationships allowed interpretation of host-pathogen interaction as well as quantification of both cultivar resistance and isolate virulence. This analysis indicated that both.flax cultivars and pathogen isolates may differ only in the quantitative aspects of resistance and virulence and not in their biochemical pathways. Analysis of field data revealed that, cultivar X year was consistently a nonsignificant source of variation. On the other hand, cultivar X location interaction was either a significant (P ≤ 0.05), or very highly significant (P ≤ 0.001) source of variation with the exception of one data set. The amount of isozymic variation among isolates of F. oxysporum f.sp. lini is adequate for the application of numerical taxonomy on these isolates

Molecular evolution of fungicide resistance in Blumeria graminis

Blumeria graminis, a powdery mildew pathogen which infects many wild grasses and cereals across the world, can cause significant losses in cereals. Applying fungicides is a main method for control, but resistance to quinone outside inhibitors and many triazole fungicides already occurs in B. graminis, and few other effective fungicides are available. In this thesis, isolates were characterised from an outbreak of B. graminis f. sp. tritici (Bgt) on wheat where three major fungicides had lost effectiveness: cyflufenamid (Cyflamid), fenpropimorph (Corbel), and prothioconazole (Proline). All isolates from the study site were completely resistant to cyflufenamid at the recommended field rate. Additionally, isolates sampled following two sprays of fenpropimorph, had significantly lower sensitivity than field isolates. RNA sequencing was used to identify the spindle assembly checkpoint protein MAD1 as a candidate target of cyflufenamid, implying that the mode of action of cyflufenamid may be to inhibit mitosis. A candidate mutation in MAD1 causing cyflufenamid resistance was also discovered. Sequencing the Erg24 gene in isolates sensitive or resistant to fenpropimorph identified a mutation that may confer resistance in Bgt, which was subsequently confirmed by site-directed mutagenesis of yeast, and a different Erg24 mutation was found in B. graminis f. sp. hordei, the barley mildew pathogen. Multiple copies of the Cyp51 (Erg11) gene were identified in Bgt isolates. Some isolates with elevated resistance were heteroallelic, carrying both wild-type and mutant Cyp51 genes. Triazole-resistant isolates had greater expression of Cyp51 than more sensitive isolates, as did UK isolates compared to those from the USA. In summary, this thesis updates knowledge of resistance to currently available fungicides and their modes of action against powdery mildew. This is important in helping to reveal how resistance to fungicides occurs. In turn, this knowledge can contribute to the discovery of new fungicides and to using new and existing chemicals more effectively