Composite Differential Evolution for Constrained Evolutionary Optimization

When solving constrained optimization problems (COPs) by evolutionary algorithms, the search algorithm plays a crucial role. In general, we expect that the search algorithm has the capability to balance not only diversity and convergence but also constraints and objective function during the evolution. For this purpose, this paper proposes a composite differential evolution (DE) for constrained optimization, which includes three different trial vector generation strategies with distinct advantages. In order to strike a balance between diversity and convergence, one of these three trial vector generation strategies is able to increase diversity, and the other two exhibit the property of convergence. In addition, to accomplish the tradeoff between constraints and objective function, one of the two trial vector generation strategies for convergence is guided by the individual with the least degree of constraint violation in the population, and the other is guided by the individual with the best objective function value in the population. After producing offspring by the proposed composite DE, the feasibility rule and the ϵ constrained method are combined elaborately for selection in this paper. Moreover, a restart scheme is proposed to help the population jump out of a local optimum in the infeasible region for some extremely complicated COPs. By assembling the above techniques together, a constrained composite DE is proposed. The experiments on two sets of benchmark test functions with various features, i.e., 24 test functions from IEEE CEC2006 and 18 test functions with 10 dimensions and 30 dimensions from IEEE CEC2010, have demonstrated that the proposed method shows better or at least competitive performance against other state-of-the-art methods

Simulated Annealing

The book contains 15 chapters presenting recent contributions of top researchers working with Simulated Annealing (SA). Although it represents a small sample of the research activity on SA, the book will certainly serve as a valuable tool for researchers interested in getting involved in this multidisciplinary field. In fact, one of the salient features is that the book is highly multidisciplinary in terms of application areas since it assembles experts from the fields of Biology, Telecommunications, Geology, Electronics and Medicine

A framework for multi-objective optimisation based on a new self-adaptive particle swarm optimisation algorithm

This paper develops a particle swarm optimisation (PSO) based framework for multi-objective optimisation (MOO). As a part of development, a new PSO method, named self-adaptive PSO (SAPSO), is first proposed. Since the convergence of SAPSO determines the quality of the obtained Pareto front, this paper analytically investigates the convergence of SAPSO and provides a parameter selection principle that guarantees the convergence. Leveraging the proposed SAPSO, this paper then designs a SAPSO-based MOO framework, named SAMOPSO. To gain a well-distributed Pareto front, we also design an external repository that keeps the non-dominated solutions. Next, a circular sorting method, which is integrated with the elitist-preserving approach, is designed to update the external repository in the developed MOO framework. The performance of the SAMOPSO framework is validated through 12 benchmark test functions and a real-word MOO problem. For rigorous validation, the performance of the proposed framework is compared with those of four well-known MOO algorithms. The simulation results confirm that the proposed SAMOPSO outperforms its contenders with respect to the quality of the Pareto front over the majority of the studied cases. The non-parametric comparison results reveal that the proposed method is significantly better than the four algorithms compared at the confidence level of 90% over the 12 test functions

A Framework for Constrained Optimization Problems Based on a Modified Particle Swarm Optimization

This paper develops a particle swarm optimization (PSO) based framework for constrained optimization problems (COPs). Aiming at enhancing the performance of PSO, a modified PSO algorithm, named SASPSO 2011, is proposed by adding a newly developed self-adaptive strategy to the standard particle swarm optimization 2011 (SPSO 2011) algorithm. Since the convergence of PSO is of great importance and significantly influences the performance of PSO, this paper first theoretically investigates the convergence of SASPSO 2011. Then, a parameter selection principle guaranteeing the convergence of SASPSO 2011 is provided. Subsequently, a SASPSO 2011-based framework is established to solve COPs. Attempting to increase the diversity of solutions and decrease optimization difficulties, the adaptive relaxation method, which is combined with the feasibility-based rule, is applied to handle constraints of COPs and evaluate candidate solutions in the developed framework. Finally, the proposed method is verified through 4 benchmark test functions and 2 real-world engineering problems against six PSO variants and some well-known methods proposed in the literature. Simulation results confirm that the proposed method is highly competitive in terms of the solution quality and can be considered as a vital alternative to solve COPs

Macroevolutionary analysis of Primates with special reference to the genus Homo

The present thesis focusses on fossil Primates, their ecological characterization, morphological evolution and diversification, and an array of new tools to study their anatomical features. The text is divided in three different parts, presenting a collection of either published or submitted manuscripts. The first part regards the morphological adaptation and diversification of Primates. The inaugural paper (“Macroevolutionary trends of brain size in primates”, Melchionna et al., under review) deals with the identification and the analysis of macroevolutionary trends in brain size evolution in Primates. We applied Phylogenetic Ridge Regression (RRphylo) to found possible shifts in morphological rates and their temporal trend. Furthermore, we computed diversification rates (DR). We found a significant increase in encephalization quotient (EQ) rates in the hominins group with an overall increase in EQ values. We found a significant correlation between DR and both EQ rates EQ values. There is also a linear relationship between speciation and extinction rates. Eventually, we found an increase in speciation rates and a reduction in extinction rates with an increase in EQ values. The second paper (“Unexpectedly rapid evolution of mandibular shape in hominins”; Raia et al., 2018) is about the evolution of mandibular shape from ancient primates to the genus Homo. We used the Geometric Mophometrics and the Phylogenetic Ridge Regression to compute evolutionary rates in mandibular morphology. We found that mandible shape evolution in hominins is exceptionally rapid as compared to any other primate clade. In the second part of the thesis I introduce new advances in the field of the Virtual Anthropology. The first is a new protocol to obtain three-dimensional reconstruction of inner and outer surfaces of fossil specimens (“Reproducing the internal and external anatomy of fossil bones: Two new automatic digital tools”; Profico et al., 2018). By using the R software platform, we developed two automatic tools to reproduce the internal and external structures of bony elements. The first method, Computer‐Aided Laser Scanner Emulator (CA‐LSE), provides the reconstruction of the external portions of a 3D mesh by simulating the action of a laser scanner. The second method, Automatic Segmentation Tool for 3D objects (AST‐3D), performs the digital reconstruction of anatomical cavities. Both methods are embedded in the packages “Arothron” (Profico et al., 2018) and "Morpho" (Schlager, 2017). The second protocol presented in this section is about the reconstruction of the original shape of fossil bones damaged and deformed by taphonomical processes (“A new tool for digital alignment in Virtual Anthropology”; Profico et al., 2018). We developed a new, semi-automatic alignment R software, Digital Tool for Alignment (DTA). This tool uses the shape information contained in a reference sample to find the best alignment solution for the disarticulated regions. The third part of the thesis focusses on Homo, and in particularl on the relationship between Homo neanerthalesis and Homo sapiens. The first paper of this section is about the status of the Neanderthal niche fragmentation toward their demise (“Fragmentation of Neanderthals' pre-extinction distribution by climate change”; Melchionna et al., 2018). By using Species Distribution Models, and a habitat fragmentation analysis, we reconstructed the ecological niche of both human species. We found Homo sapiens had greater ecological plasticity over Neanderthals, which probably allowed this species to better react to climatic worsening at 44 and then at 40 ka. However, Neanderthals potential habitat appears to be very reduced and fragmented during the last phase of their occupation. The second paper of this last section regards the role of Homo sapiens in the Late Pleistocene megafauna extinction (“The well-behaved killer: Late Pleistocene humans in Eurasia were significantly associated with living megafauna only”; Carotenuto et al., 2018). Starting from a rich faunal and archaeological database, and by using SDMs, we obtained megafauna and humans occurrence probability maps over the last 40 ka in Eurasia. Then, we divided species in ecological groups (i.e., body size and feeding category combined). We evaluated their geographical overlap to human range and the species suitability in the core area of Homo sapiens. The results indicated that the extinct megafauna was rare within humans' range and Palaeolithic hunters had stronger association to extant rather than extinct herbivorous species

On robust and adaptive soft sensors.

In process industries, there is a great demand for additional process information such as the product quality level or the exact process state estimation. At the same time, there is a large amount of process data like temperatures, pressures, etc. measured and stored every moment. This data is mainly measured for process control and monitoring purposes but its potential reaches far beyond these applications. The task of soft sensors is the maximal exploitation of this potential by extracting and transforming the latent information from the data into more useful process knowledge. Theoretically, achieving this goal should be straightforward since the process data as well as the tools for soft sensor development in the form of computational learning methods, are both readily available. However, contrary to this evidence, there are still several obstacles which prevent soft sensors from broader application in the process industry. The identification of the sources of these obstacles and proposing a concept for dealing with them is the general purpose of this work. The proposed solution addressing the issues of current soft sensors is a conceptual architecture for the development of robust and adaptive soft sensing algorithms. The architecture reflects the results of two review studies that were conducted during this project. The first one focuses on the process industry aspects of soft sensor development and application. The main conclusions of this study are that soft sensor development is currently being done in a non-systematic, ad-hoc way which results in a large amount of manual work needed for their development and maintenance. It is also found that a large part of the issues can be related to the process data upon which the soft sensors are built. The second review study dealt with the same topic but this time it was biased towards the machine learning viewpoint. The review focused on the identification of machine learning tools, which support the goals of this work. The machine learning concepts which are considered are: (i) general regression techniques for building of soft sensors; (ii) ensemble methods; (iii) local learning; (iv) meta-learning; and (v) concept drift detection and handling. The proposed architecture arranges the above techniques into a three-level hierarchy, where the actual prediction-making models operate at the bottom level. Their predictions are flexibly merged by applying ensemble methods at the next higher level. Finally from the top level, the underlying algorithm is managed by means of metalearning methods. The architecture has a modular structure that allows new pre-processing, predictive or adaptation methods to be plugged in. Another important property of the architecture is that each of the levels can be equipped with adaptation mechanisms, which aim at prolonging the lifetime of the resulting soft sensors. The relevance of the architecture is demonstrated by means of a complex soft sensing algorithm, which can be seen as its instance. This algorithm provides mechanisms for autonomous selection of data preprocessing and predictive methods and their parameters. It also includes five different adaptation mechanisms, some of which can be applied on a sample-by-sample basis without any requirement to store the on-line data. Other, more complex ones are started only on-demand if the performance of the soft sensor drops below a defined level. The actual soft sensors are built by applying the soft sensing algorithm to three industrial data sets. The different application scenarios aim at the analysis of the fulfilment of the defined goals. It is shown that the soft sensors are able to follow changes in dynamic environment and keep a stable performance level by exploiting the implemented adaptation mechanisms. It is also demonstrated that, although the algorithm is rather complex, it can be applied to develop simple and transparent soft sensors. In another experiment, the soft sensors are built without any manual model selection or parameter tuning, which demonstrates the ability of the algorithm to reduce the effort required for soft sensor development. However, if desirable, the algorithm is at the same time very flexible and provides a number of parameters that can be manually optimised. Evidence of the ability of the algorithm to deploy soft sensors with minimal training data and as such to provide the possibility to save the time consuming and costly training data collection is also given in this work

How Important Is Land-Based Foraging To Polar Bears (ursus Maritimus) During The Ice-Free Season In Western Hudson Bay? An Examination Of Dietary Shifts, Compositional Patterns, Behavioral Observations And Energetic Contributions

Trophic mismatches between predators and their prey are increasing as climate change causes decoupling of phenological relationships. Predators linked to the life histories of a particular prey will have a more difficult time persisting through environmental change unless they can alter their behavior to maintain the historical match or possess the ability to pursue alternate prey. Arctic predators typically possess flexible foraging strategies to survive in the labile environment, however, quantifying the limits of those strategies can be difficult when life history information is incomplete. In such cases, piecing together different aspects of a predator\u27s foraging behavior, particularly when environmental effects are thought to induce the most nutritional stress, can serve as a basis to understand the species\u27 resiliency in response to climate changes. Climate change is impacting the Hudson Bay region faster than any other portion of Arctic North America. As a consequence, polar bears (Ursus maritimus) in western Hudson Bay, near the southern extent of their range, are already experiencing a phenological mismatch with their primary prey, ringed seals (Phoca hispida). These polar bears have relied on the energy stores amassed from hunting seal pups in spring to sustain them through the ice-free season on land for 4 to 5 months. As climate change causes the ice in Hudson Bay to melt earlier in spring, polar bears are projected to have less time to hunt seal pups on the sea ice, leaving them with smaller energy reserves to sustain them for longer periods on land. As a result, body condition is expected to deteriorate, leading to eventual declines in reproduction and survival, unless alternative energy sources are utilized. Polar bears currently hunt and consume a variety of foods during the ice-free season. Few believe, however, that such foraging will compensate for projected energy deficits from lost seal hunting opportunities. This skepticism stems from the perceptions that polar bears are specially adapted to hunting seals on the ice, the behavior has always occurred, but only a few polar bears partake in it, breath-based carbon-isotope analyses suggest that energy expended on land is solely of marine (i.e., seal) origin, pursuing animals on land would be too energetically expensive for polar bears to experience any net gain and there is not enough energy in land-based food to compensate all polar bears in western Hudson Bay for the energy available from seals on the ice. Many of these arguments are premised on the idea that past (and even present) foraging behaviors are representative of how polar bears will respond to future climate-related changes. Alternatively, the past behaviors may have represented optimal foraging strategies when seals were relatively abundant and easy to catch. Rather than tie the polar bears\u27 fate directly to deteriorating ice conditions and thus availability of a single prey, I consider a more mechanistic approach to evaluating polar bears\u27 reaction to climate changes. In light of the shared genetic legacy with grizzly bears, I analyze different aspects of polar bears\u27 current foraging behavior, as well as known physiological and energetic constraints, to consider an alternative future scenario by which polar bears might persist consuming land-based food during the ice-free season. I explore different aspects of land-based foraging and address aforementioned concerns regarding the potential value of terrestrial foods in a series of interrelated chapters. In the first chapter, I develop a comprehensive inventory of foods polar bears currently consume on land and compare them to those consumed approximately 40 years earlier, prior to the onset of climate changes, using morphological scat analysis. Changes in the polar bear diet between time periods are compared to changes in availability of specific prey items in the region (Chapter 1) as well as where and when they currently occur most abundantly in the landscape (Chapter 2). Based on compositional patterns, I explore the extent of diet mixing and its implications for weight gain (or rate of weight loss, Chapter 2). In addition to long-term changes in abundance that have made Lesser Snow Geese (Chen caerulescens caerulescens) more available since the 1960s, temporal shifts in their incubation period and earlier ice-breakup is creating a new trophic match between arriving polar bears and eggs. The potential energy available from this increasingly accessible resource and its implications for energy compensation are discussed in Chapter 3. In Chapter 4, I provide total energy values for populations of novel animal foods (snow geese, eggs, caribou (Rangifer tarandus) and vegetation (berries, Lyme grass seed heads (Leymus arenarius) that polar bears consume on land and determine what amounts of each, alone or in combination, would prevent adult males from starving to death as the ice-free season expands to a 180 days as predicted by Molnár et al. (2010). In Chapter 5, I reexamine available data on the energetic costs of locomotion at different speeds, develop a new predictive model and challenge past assertions by Lunn and Stirling (1985) that energetic inefficiencies would prevent a polar bear from profiting after a sustained chase. In Chapter 6, I present unpublished observations of polar bears foraging from land and in open water from the Hudson Bay Project archives and my personal observations. I describe different evolutionary pathways for the observed behavior in light of their recent divergence from grizzly bears and the implications of each for future polar bear persistence

Impacts of a specialist diet on aardwolf ecology

The diet of an animal plays a fundamental role in its ecology, and the consequence of a specific diet may be more pronounced in mammals with a specialised diet that are more reliant on a specific food type. This can have a dramatic effect on its activity patterns, home range size and the interaction with heterospecifics. Investigating the diet of specialist mammals and the subsequent effects it will have on their ecology is thus vital to the management and subsequent conservation of the species, and crucial to our understanding of how the animal can survive and reproduce. In this thesis I investigate the effect that the diet of the aardwolf, a highly specialised myrmecophage, has on its ecology. Aardwolves feed predominantly on one genus of termite, Trinervoides spp., and are thus extremely dependent on the abundance and distribution of this arthropod. I firstly investigated the effect of temperature and rainfall on arthropod abundance and diversity, and further investigated the variation of arthropod abundance and diversity across the four habitat types at study site. This is one of a few studies that have been conducted on arthropod abundance and diversity in an arid environment and the findings show that in an arid environment arthropods are mainly influenced by temperature rather than rainfall. This is in contrast to studies in temperate and forest habitats where rainfall is the most important abiotic factor determining the abundance and diversity of arthropod assemblages. Habitat type still plays a major role in the abundance and diversity of arthropods, and habitat types that are more complex and diverse have both a higher diversity, and abundance of arthropods than other habitats. Due to the absence of prey items during the colder months of the year I investigated the diet of aardwolves to see if they display a switch in diet. This included an investigation into the seasonal variation of diet from a detailed scat analysis, using a newly developed method to assess scat content. The analysis of scats revealed that, contrary to previous studies, aardwolves showed no switch in diet and continued to feed on Trinervitermes. Using the data from the scat analyses and the information from the abundance and diversity of arthropods at the study site I expanded the study to investigate the functional responses of the aardwolf to change in prey abundance at the locality. Aardwolves demonstrate a Type I functional response to changes in prey abundance, a response that is normally found in plankton feeders. The expected functional response for specialist animals would be Type II response, and I propose that the Type I response seen in aardwolves is probably as a result of a limited handling time which reduces time spent foraging. The abundance of termites thus had a clear effect on the diet of aardwolves, showing that they feed on fewer when they are unavailable, and as such I investigated the effect of termite densities on home range sizes. The number of termite mounds in a home range influenced the size of the home range, and aardwolves with larger home ranges had a lower density of termite mounds. In contrast to previous studies, large overlaps between neighbouring individuals were recorded and indeed three male aardwolves shared a common den. I propose that the reason behind the overlap of home ranges is that a higher prey abundance during my study period occurred and as a consequence aardwolves did not need to defend an area to protect this resource. T. trinervoides has thus played a keystone role in driving the biology of the aardwolf and shaping many aspects of its ecology.Thesis (PhD)--University of Pretoria, 2021.South African Research Chair Initiative chair of Mammal Behavioural Ecology and PhysiologyZoology and EntomologyPhDUnrestricte

Life on the edge: exploring the effects of urbanisation on the foraging ecology and ecotoxicology of caracals

The continuing loss of natural habitat to a broad range of human activities is one of the main drivers of biodiversity decline worldwide and a defining feature of the Anthropocene. However, some opportunistic, generalist species may benefit from transformed landscapes through, for example, the absence of apex predators or access to human-subsidised food resources. These benefits may thus offset the higher mortality and health risks typically associated with human-dominated landscapes. To understand the cost-benefit trade-offs of life on the urban edge, I investigated the foraging ecology and ecotoxicology of a highly adaptable medium-sized carnivore, the caracal (Caracal caracal), utilising both natural and transformed landscapes around the rapidly growing city of Cape Town, South Africa. Through a combination of scat analysis (n = 654 scats) and prey remains located at 677 GPS clusters, I quantified dietary resource use of 26 collared individuals, as well as opportunistically sampled caracals. Using a range of gut transit times, I estimated whether scat at cluster sites was from the same or an earlier feeding event, thereby increasing the overall detection of individual-specific feeding events by > 50%. While most feeding events occurred within 200 m of the urban edge of Cape Town, I found that caracals have flexible diets that largely comprise medium- to small-sized wild prey (60%), followed by human-associated species (27%), and introduced or domestic species (13%). Using a subset of the feeding and resting events (n = 326 prey remains, n = 384 scat, n = 177 resting sites) that were associated with known individuals (n = 17), I then investigated caracal resource selection using both anthropogenic and environmental factors. Additionally, I examined the behaviour of caracal at feeding clusters to determine if they respond to spatial and temporal risks associated with anthropogenic factors. I found divergent resource selection patterns based on the level of exposure to urbanisation: caracals living in the urban-dominated region of the Peninsula (n = 14; 548 feeding events) select for the urban edge, while caracals in the wildland-dominated region (n = 3; 162 feeding events) strongly avoid it. I argue that in the more urbanised region, caracals forage on or close to the urban edge because this is where the remaining low-lying wildland habitat is most productive and attractive. Consequently, caracals in heavily transformed areas, which might otherwise tend to avoid human disturbance, have habituated to human presence but reduce their risk of detection by remaining cryptic, prolonging handling time, and maintaining high feeding site fidelity where cover is available. To quantify the consequences of peri-urban foraging, I use an ecotoxicological approach to assess environmental contamination and its potential effects on caracals. It is widely reported that persistent organic pollutants (POPs), including organochlorines (OCs) such as PCBs and DDT and its metabolites, are extremely toxic, causing adverse effects on wildlife and human health. I tested blood and adipose tissues of caracals, with different diets utilising a range of natural and transformed landscapes, for exposure to commonly detected OCs. Despite restrictions on their use, I found extensive OC burdens, with 100% of adipose samples exposed to both DDT and PCBs, and 100% and 83% of blood samples exposed to DDT and PCBs respectively. Caracals using areas with a higher density of people and electrical transformers, and those using areas close to informal settlements, had higher exposure to OCs. Additionally, the use of vineyards and wetlands and a diet with a greater proportion of higher trophic level or exotic prey correlated with a higher risk of exposure to OC pollutants. Full blood analyses revealed that exposure levels to OCs were also associated with higher counts of infection-fighting cells, suggesting these compounds may affect the immune response of individuals. With time, these detrimental effects may have population-level repercussions through impacts on reproductive success and fitness. Together these findings reveal that while caracals and other medium-sized adaptable carnivores may persist within or adjacent to human transformed habitats, they still prefer natural habitat and pay a significant cost for foraging on prey species that have been contaminated by pollutants associated with urban and rural land uses. Urban edges may thus be an ecotoxicological trap, threatening the health and long-term persistence of caracals and other wildlife in this and other biodiversity hotspots. Reducing environmental contamination and limiting habitat loss to urban sprawl would benefit wildlife living on the transformed edges but requires significant improvements to both the legislation governing pollutants and the spatial planning of cities