Genetic Algorithm with Optimal Recombination for the Asymmetric Travelling Salesman Problem

We propose a new genetic algorithm with optimal recombination for the asymmetric instances of travelling salesman problem. The algorithm incorporates several new features that contribute to its effectiveness: (i) Optimal recombination problem is solved within crossover operator. (ii) A new mutation operator performs a random jump within 3-opt or 4-opt neighborhood. (iii) Greedy constructive heuristic of W.Zhang and 3-opt local search heuristic are used to generate the initial population. A computational experiment on TSPLIB instances shows that the proposed algorithm yields competitive results to other well-known memetic algorithms for asymmetric travelling salesman problem.Comment: Proc. of The 11th International Conference on Large-Scale Scientific Computations (LSSC-17), June 5 - 9, 2017, Sozopol, Bulgari

Faithful chaperones

This review describes the properties of some rare eukaryotic chaperones that each assist in the folding of only one target protein. In particular, we describe (1) the tubulin cofactors, (2) p47, which assists in the folding of collagen, (3) α-hemoglobin stabilizing protein (AHSP), (4) the adenovirus L4-100 K protein, which is a chaperone of the major structural viral protein, hexon, and (5) HYPK, the huntingtin-interacting protein. These various-sized proteins (102–1,190 amino acids long) are all involved in the folding of oligomeric polypeptides but are otherwise functionally unique, as they each assist only one particular client. This raises a question regarding the biosynthetic cost of the high-level production of such chaperones. As the clients of faithful chaperones are all abundant proteins that are essential cellular or viral components, it is conceivable that this necessary metabolic expenditure withstood evolutionary pressure to minimize biosynthetic costs. Nevertheless, the complexity of the folding pathways in which these chaperones are involved results in error-prone processes. Several human disorders associated with these chaperones are discussed

Clinical predictive factors in diabetic kidney disease progression

Diabetic kidney disease (DKD) represents a major component of the health burden associated with type 1 and type 2 diabetes. Recent advances have produced an explosion of 'novel' assay-based risk markers for DKD, though clinical use remains restricted. Although many patients with progressive DKD follow a classical albuminuria-based pathway, non-albuminuric DKD progression is now well recognized. In general, the following clinical and biochemical characteristics have been associated with progressive DKD in both type 1 and type 2 diabetes: increased hemoglobin A1c, systolic blood pressure, albuminuria grade, early glomerular filtration rate decline, duration of diabetes, age (including pubertal onset) and serum uric acid; the presence of concomitant microvascular complications; and positive family history. The same is true in type 2 diabetes for male sex category, in patients following an albuminuric pathway to DKD, and also true for the presence of increased pulse wave velocity. The following baseline clinical characteristics have been proposed as risk factors for DKD progression, but with further research required to assess the nature of any relationship: dyslipidemia (including low-density lipoprotein, total and high-density lipoprotein cholesterol); elevated body mass index; smoking status; hyperfiltration; decreases in vitamin D, hemoglobin and uric acid excretion (all known consequences of advanced DKD); and patient test result visit-to-visit variability (hemoglobin A1c, blood pressure and high-density lipoprotein cholesterol). The development of multifactorial 'renal risk equations' for type 2 diabetes has the potential to simplify the task of DKD prognostication; however, there are currently none for type 1 diabetes-specific populations. Significant progress has been made in the prediction of DKD progression using readily available clinical data, though further work is required to elicit the role of several variables, and to consolidate data to facilitate clinical implementation

A Design Framework for Metaheuristics

This paper is concerned with taking an engineering approach towards the application of metaheuristic problem solving methods, i.e. heuristics that aim to solve a wide variety of problems. How can a practitioner solve a problem using metaheuristic methods? What choices do they have, and how are these choices influenced by the problem at hand? Are there sensible universal choices which can be made, or are these choices always problem-dependent? The aim of this paper is to address questions such as these in the context of a (soft) engineering design framework for the application of metaheuristics. The aim of this framework is to make explicit the choices which a practitioner needs to make in applying these techniques, and to give some guidelines for how metaheuristics might be tuned to problems by considering different problem- and solution-types

Evolutionary Mesh Numbering: Preliminary Results

Mesh numbering is a critical issue in Finite Element Methods, as the computational cost of one analysis is highly dependent on the order of the nodes of the mesh. This paper presents some preliminary investigations on the problem of mesh numbering using Evolutionary Algorithms. Three conclusions can be drawn from these experiments. First, the results of the up-to-date method used in all FEM softwares (Gibb's method) can be consistently improved; second, none of the crossover operators tried so far (either general or problem specific) proved useful; third, though the general tendency in Evolutionary Computation seems to be the hybridization with other methods (deterministic or heuristic), none of the presented attempt did encounter any success yet. The good news, however, is that this algorithm allows an improvement over the standard heuristic method between 12% and 20% for both the 1545 and 5453-nodes meshes used as test-bed. Finally, some strange interaction between the selection scheme and the use of problem specific mutation operator was observed, which appeals for further investigation