http://www.lcc.uma.es/~eat/pdf/itor2013.pdf

Parallel metaheuristics: recent advances and new trends

Assessing species' vulnerability to climate change is a prerequisite for developing effective strategies to conserve them. The last three decades have seen exponential growth in the number of studies evaluating how, how much, why, when, and where species will be impacted by climate change. We provide an overview of the rapidly developing field of climate change vulnerability assessment (CCVA) and describe key concepts, terms, steps and considerations. We stress the importance of identifying the full range of pressures, impacts and their associated mechanisms that species face and using this as a basis for selecting the appropriate assessment approaches for quantifying vulnerability. We outline four CCVA assessment approaches, namely trait-based, correlative, mechanistic and combined approaches and discuss their use. Since any assessment can deliver unreliable or even misleading results when incorrect data and parameters are applied, we discuss finding, selecting, and applying input data and provide examples of open-access resources. Because rare, small-range, and declining-range species are often of particular conservation concern while also posing significant challenges for CCVA, we describe alternative ways to assess them. We also describe how CCVAs can be used to inform IUCN Red List assessments of extinction risk. Finally, we suggest future directions in this field and propose areas where research efforts may be particularly valuable.

/pdf/climate-change-vulnerability-assessment-of-species-1r55mskj5h.pdf

Climate change vulnerability assessment of species

Ant colony optimization (ACO) is a well-known swarm intelligence method, inspired in the social behavior of ant colonies for solving optimization problems. When facing large and complex problem instances, parallel computing techniques are usually applied to improve the efficiency, allowing ACO algorithms to achieve high quality results in reasonable execution times, even when tackling hard-to-solve optimization problems. This work introduces a new taxonomy for classifying software-based parallel ACO algorithms and also presents a systematic and comprehensive survey of the current state-of-the-art on parallel ACO implementations. Each parallel model reviewed is categorized in the new taxonomy proposed, and an insight on trends and perspectives in the field of parallel ACO implementations is provided.

/pdf/a-survey-on-parallel-ant-colony-optimization-3oe1v4f1eg.pdf

A survey on parallel ant colony optimization

Optimization techniques have been indispensable for designing high-performance meta-devices targeted to a wide range of applications. In fact, today optimization is no longer an afterthought and is a fundamental tool for many optical and RF designers. Still, many devices presented in recent literature do not take advantage of optimization techniques. This paper seeks to address this by presenting both an introduction to and a review of several of the most popular techniques currently used for meta-device design. Additionally, emerging techniques like topology optimization and multi-objective optimization and their context to device design are thoroughly discussed. Moreover, attention is given to future directions in meta-device optimization such as surrogate-modeling and deep learning which have the potential to disrupt the fields of optical and radio frequency (RF) inverse-design. Finally, many design examples from the literature are presented and a flow-chart that provides guidance on how best to apply these optimization algorithms to a given problem is provided for the reader.

Review of numerical optimization techniques for meta-device design [Invited]

Abtract
1.Scientific research increasingly calls for open-source software that is flexible, interactive, and expandable, while providing methodological guidance and reproducibility. Currently, many analyses in ecology are implemented with “black box” graphical user interfaces that lack flexibility or command-line interfaces that are infrequently used by non-specialists.

2.To help remedy this situation in the context of species distribution modeling, we created Wallace, an open and modular application with a richly documented graphical user interface to underlying R scripts that is flexible and highly interactive.

3.Wallace guides users from acquiring and processing data to building models and examining predictions. Additionally, it is designed to grow via community contributions of new modules to expand functionality. All results are downloadable, along with code to reproduce the analysis.

4.Wallace provides an example of an innovative platform to increase access to cutting-edge methods and encourage plurality in science and collaboration in software development.

This article is protected by copyright. All rights reserved.

https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12945

Wallace: A flexible platform for reproducible modeling of species niches and distributions built for community expansion

Advances in computing power and infrastructure, increases in the number and size of ecological and environmental datasets, and the number and type of data collection methods, are revolutionizing the field of Ecology. To integrate these advances, virtual laboratories offer a unique tool to facilitate, expedite, and accelerate research into the impacts of climate change on biodiversity. We introduce the uniquely cloud-based Biodiversity and Climate Change Virtual Laboratory (BCCVL), which provides access to numerous species distribution modelling tools; a large and growing collection of biological, climate, and other environmental datasets; and a variety of experiment types to conduct research into the impact of climate change on biodiversity.Users can upload and share datasets, potentially increasing collaboration, cross-fertilisation of ideas, and innovation among the user community. Feedback confirms that the BCCVL's goals of lowering the technical requirements for species distribution modelling, and reducing time spent on such research, are being met. BCCVL facilitates and expedites modelling of climate change's impact on biodiversity.BCCVL integrates numerous species distribution modelling tools and myriad datasets.BCCVL negates the need for advanced programming and modelling expertise.BCCVL allows for increases in productivity and complexity of experimental design.BCCVL facilitates the sharing of data promoting transparency in the research process.

The Biodiversity and Climate Change Virtual Laboratory

Radio Frequency IDentification (RFID) technology is increasingly being used to uniquely identify objects. An important component of RFID systems is the design of the antenna - which usually takes the form of a compacted meander line. This task becomes an optimisation problem as different designs will have different efficiencies and resonant frequencies. In this paper, we explore the use of a multi-objective version of ant colony system. This constructive meta-heuristic, as shown, is highly suitable for this problem.

/pdf/optimising-efficiency-and-gain-of-small-meander-line-rfid-2iolxct30a.pdf

Optimising efficiency and gain of small meander line RFID antennas using ant colony system

A method increasingly used to uniquely identify objects (be they pieces of luggage, transported goods or inventory items in shops and warehouses), is Radio Frequency IDentification (RFID). One of the most important components of RFID systems is the antenna and its design is critical to the utility of such tracking systems. Design engineers have traditionally constructed small antennas using their knowledge and intuition, as there is no simple analytical solution relating antenna structure to performance. This, however, does not guarantee optimal results, particularly for larger, more complex antennas. The problem is ideally suited to automated methods of optimisation. This chapter presents an overview of the automatic design of antennas using the meta-heuristic known as Ant Colony Optimisation (ACO). Apart from a description of the necessary mechanics ACO needs to effectively solve this problem, a novel local search refinement operator and a multi-objective version of the problem are also described. The latter is used to optimise both antenna efficiency and resonant frequency. Computational results for a range of antenna sizes show that ACO is a very effective design tool for RFID antennas.

Using Ant Colony Optimisation to Construct Meander-Line RFID Antennas

The efficient design of meander line antennas for RFID devices is a significant real-world problem. Traditional manual tuning of antenna designs is becoming impractical for larger problems. Thus the use of automated techniques, in the form of combinatorial search algorithms, is a necessity. Ant colony system (ACS) is a very efficient meta-heuristic that is commonly used to solve path construction problems. Apart from its own native search capacity, ACS can be dramatically improved by combining it with local search strategies. As shown in this paper, applying local search as a form of structure refinement to RFID meander line antennas delivers effective antenna structures. In particular, we use the operator known as backbite, that has had previous application in the construction of self-avoiding walks and compact polymer chains. Moreover, we apply it in a novel, hierarchical manner that allows for good sampling of the local search space. Its use represents a significant improvement on results obtained previously.

/pdf/local-search-for-ant-colony-system-to-improve-the-efficiency-25gh4x16gy.pdf

Local search for Ant colony system to improve the efficiency of small meander line RFID antennas

XMPP (XML Messaging and Presence Protocol), also known as Jabber, is a popular instant messaging protocol that uses XML streams for communication. Due to it's high extensibility, XMPP is very easy to adapt to other uses than instant messaging. Furthermore, announcing of presence state makes it ideal for highly volatile environments. This paper outlines the use of XMPP for a grid-like computation environment. The biggest advantage of this setup was that available computing resources, such as laboratory computers, could be connected easily and used similarly to a grid. The application example described in this paper uses Ant Colony System (ACS) optimisation and the NEC-tool to optimise RFID antennas, involving computing the efficiency and resonant frequency of a large number of different antenna structures.

/pdf/using-xmpp-for-ad-hoc-grid-computing-an-application-example-33vnrs330q.pdf

Gerhard Weis

Papers

The Biodiversity and Climate Change Virtual Laboratory

Optimising efficiency and gain of small meander line RFID antennas using ant colony system

Using Ant Colony Optimisation to Construct Meander-Line RFID Antennas

Local search for Ant colony system to improve the efficiency of small meander line RFID antennas

Using XMPP for ad-hoc grid computing - an application example using parallel ant colony optimisation