Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms 1: A Unified Formulation

In optimization, multiple objectives and constraints cannot be handled independently of the underlying optimizer. Requirements such as continuity and differentiability of the cost surface and yet another conflicting element to the decision process. While "better" solutions should be rated higher than "worse" ones, the resulting cost landscape must also comply with such requirements. Evolutionary algorithms (EA'S), which have found application in many areas not amenable to optimization by other methods, possess many characteristics desirable in a multiobjective optimizer, most notably at the concerted handling of multiple candidate solutions. However, EA's are essentially unconstrained search techniques which require the assignment of a scalar measure of quality or fitness to such candidate solutions. After reviewing current evolutionary approaches to multiobjective constrained optimization, the paper proposes that fitness assignment be interpreted as, or at least related to, a multicriterion decision process. A suitable decision making framework based on goals and priorities is subsequently formulated in terms of a relational operator, characterized and shown to encompass a number of simpler decision strategies. Finally, the ranking of an arbitrary number of candidates is considered. The effect of preference changes on the cost surface seen by an EA is illustrated graphically for a simple problem. The paper concludes with the formulation of a multiobjective genetic algorithm based on the proposed decision strategy. Niche formation techniques are used to promote diversity among preferable candidates and progressive articulation of preferences is shown to be possible as long as the genetic algorithm can recover from abrupt changes in the cost landscape

Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms II: Application Example

The evolutionary approach to multiple function optimization formulated in the first part of the paper (1) is applied to the optimization of the low-pressure spool speed governor of a Pegasus turbine engine. This study illustrates how a technique such as the mUltiobjective Genetic Algorithm can be applied and exemplifies how design requirements can be defined as the algorithm runs. Several objective functions and associated goals express design concerns in direct form, i.e., as the designer would state them. While such a designer-orientated formulation is very attractive, its practical usefulness depends heavily on the ability to search and optimize cost surfaces in such a class much broader than usual, as already provided to a large extent by the Genetic Algorithm (GA). The two instances of the problem studied, demonstrate the need for preference articulation in cases where many and highly competing objects lead to a non dominated set too large for a finite population to sample effectively. Further, it is sown that only a very small portion of the non-dominated set is of practical relevance, which further substantiates the need to supply preference information to the GA. The paper concludes with a discussion of the results

Automatic structures for semigroup constructions

We survey results concerning automatic structures for semigroup constructions, providing references and describing the corresponding automatic structures. The constructions we consider are: free products, direct products, Rees matrix semigroups, Bruck-Reilly extensions and wreath products.Comment: 22 page

Identifying the Structure of Non-Linear Dynamic Systems Using Multiobjective Genetic Programming

A method for identifying the structure of non-linear polynomial dynamic models is presented. This approach uses an evolutionary algorithm, Genetic Programming, in a multiobjective fashion to generate global models which describe the dynamic behaviour of the non-linear system under investigation. The introduction of the validation stage of system identification into the multiobjective tool is also explored, in order to direct the identification process to a set of global models of the system

The role of forest genetic resources in responding to biotic and abiotic factors in the context of anthropogenic climate change

The current distribution of forest genetic resources on Earth is the result of a combination of natural processes and human actions. Over time, tree populations have become adapted to their habitats including the local ecological disturbances they face. As the planet enters a phase of human-induced climate change of unprecedented speed and magnitude, however, previously locally-adapted populations are rendered less suitable for new conditions, and ‘natural’ biotic and abiotic disturbances are taken outside their historic distribution, frequency and intensity ranges. Tree populations rely on phenotypic plasticity to survive in extant locations, on genetic adaptation to modify their local phenotypic optimum or on migration to new suitable environmental conditions. The rate of required change, however, may outpace the ability to respond, and tree species and populations may become locally extinct after specific, but as yet unknown and unquantified, tipping points are reached. Here, we review the importance of forest genetic resources as a source of evolutionary potential for adaptation to changes in climate and other ecological factors. We particularly consider climate-related responses in the context of linkages to disturbances such as pests, diseases and fire, and associated feedback loops. The importance of management strategies to conserve evolutionary potential is emphasised and recommendations for policy-makers are provided

The holy blood and the holy grail: Myths of scientific racism and the pursuit of excellence in sport

Despite the continuing publication of research that suggests there is no scientific basis to 'race' as a biological category, theories of racial difference continue to be invoked within sport to explain the perceived dominance of black athletes. In the case of John Entine's controversial 'Taboo: why black athletes dominate sports and why we are afraid to talk about it' or undergraduate textbooks that suggest 'racial differences' in physique may significantly affect athletic performance, scientific racism is normalised in sport. In this article, the relationship between scientific racism and sport will be examined. Qualitative research with current sport scientists is used to investigate the socio-ethical tensions within the subject field of sport science between professionalism, scientism and the demand from external interests to produce results that help people in sport win medals. It will be shown that these tensions, combined with the history of race as a category in sport science, combine to create the discourse of scientific knowledge that reflects, rather than challenges, folk genetics of black athletic physicality

Exogenous NG-hydroxy-l-arginine causes nitrite production in vascular smooth muscle cells in the absence of nitric oxide synthase activity

AbstractNitric oxide (NO) production from exogenous NG-hydroxy-l-arginine (OH-l-Arg) was investigated in rat aortic smooth muscle cells in culture by measuring nitrite accumulation in the culture medium. As well, the interaction between OH-l-Arg and l-arginine uptake via the y+ cationic amino acid transporter was studied. In cells without NO-synthase activity, OH-l-Arg (1–1000 μM) induced a dose-dependent nitrite production with a half-maximal effective concentration (EC50) of 18.0 ± 1.5 μM (n = 4–7). This nitrite accumulation was not inhibited by the NO-synthase inhibitor NG-nitro-l-arginine methyl ester, l-NAME (300 μM). In contrast, it was abolished by miconazole (100 μM), an inhibitor of cytochrome P450. Incubation of vascular smooth muscle cells with LPS (10 μgml) induced an l-name inhibited nitrite accumulation, but did not enhance the OH-l-Arg induced nitrite production. OH-l-Arg and other cationic amino acids, L-lysine and l-ornithine, competitively inhibited [3H]-l-arginine uptake m rat aortic smooth muscle cells, with inhibition constants of 195 ± 23 μM(n = 12), 260 ± 40 μM(n= 5) and 330 ± 10 μM(n = 5), respectively. These results show that OH-l-Arg is recognized by the cationic l-amino acid carrier present in vascular smooth muscle cells and can be oxidized to NO and nitrite in these cells in the absence of NO-synthase, probably by cytochrome P450 or by a reaction involving a cytochrome P450 byproduct

Melting and Dimensionality of the Vortex Lattice in Underdoped YBa2Cu3O6.60

Muon spin rotation measurements of the magnetic field distribution in the vortex state of the oxygen deficient high-Tc superconductor YBa{2}Cu{3}O{6.60} reveal a vortex-lattice melting transition at much lower temperature than that in the fully oxygenated material. The transition is best described by a model in which adjacent layers of ``pancake'' vortices decouple in the liquid phase. Evidence is also found for a pinning-induced crossover from a solid 3D to quasi-2D vortex lattice, similar to that observed in the highly anisotropic superconductor Bi{2+x}Sr{2-x}CaCu{2}O{8+y}.Comment: 8 pages, 4 figures, 5 postscript file

Nuclear Parity-Violation in Effective Field Theory

We reformulate the analysis of nuclear parity-violation (PV) within the framework of effective field theory (EFT). To order Q, the PV nucleon-nucleon (NN) interaction depends on five a priori unknown constants that parameterize the leading-order, short-range four-nucleon operators. When pions are included as explicit degrees of freedom, the potential contains additional medium- and long-range components parameterized by PV piNN couplings. We derive the form of the corresponding one- and two-pion-exchange potentials. We apply these considerations to a set of existing and prospective PV few-body measurements that may be used to determine the five independent low-energy constants relevant to the pionless EFT and the additional constants associated with dynamical pions. We also discuss the relationship between the conventional meson-exchange framework and the EFT formulation, and argue that the latter provides a more general and systematic basis for analyzing nuclear PV.Comment: 67 Page Latex file with typos correcte

Liger : a cross-platform open-source integrated optimization and decision-making environment

Real-world optimization problems involving multiple conflicting objectives are commonly best solved using multi-objective optimization as this provides decision-makers with a family of trade-off solutions. However, the complexity of using multi-objective optimization algorithms often impedes the optimization process. Knowing which optimization algorithm is the most suitable for the given problem, or even which setup parameters to pick, requires someone to be an optimization specialist. The lack of supporting software that is readily available, easy to use and transparent can lead to increased design times and increased cost. To address these challenges, Liger is presented. Liger has been designed for ease of use in industry by non-specialists in optimization. The user interacts with Liger via a visual programming language to create an optimization workflow, enabling the user to solve an optimization problem. Liger contains a novel optimization library known as Tigon. The library utilizes the concept of design patterns to enable the composition of optimization algorithms by making use of simple reusable operator nodes. The library offers a varied range of multi-objective evolutionary algorithms which cover different paradigms in evolutionary computation; and supports a wide variety of problem types, including support for using more than one programming language at a time to implement the optimization model. Additionally, Liger functionality can be easily extended by plugins that provide access to state-of-the-art visualization tools and are responsible for managing the graphical user interface. Lastly, new user-driven interactive capabilities are shown to facilitate the decision-making process and are demonstrated on a control engineering optimization problem