215 research outputs found

    On multimodality of obnoxious faclity location models

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    Obnoxious single facility location models are models that have the aim to find the best location for an undesired facility. Undesired is usually expressed in relation to the so-called demand points that represent locations hindered by the facility. Because obnoxious facility location models as a rule are multimodal, the standard techniques of convex analysis used for locating desirable facilities in the plane may be trapped in local optima instead of the desired global optimum. It is assumed that having more optima coincides with being harder to solve. In this thesis the multimodality of obnoxious single facility location models is investigated in order to know which models are challenging problems in facility location problems and which are suitable for site selection. Selected for this are the obnoxious facility models that appear to be most important in literature. These are the maximin model, that maximizes the minimum distance from demand point to the obnoxious facility, the maxisum model, that maximizes the sum of distance from the demand points to the facility and the minisum model, that minimizes the sum of damage of the facility to the demand points. All models are measured with the Euclidean distances and some models also with the rectilinear distance metric. Furthermore a suitable algorithm is selected for testing multimodality. Of the tested algorithms in this thesis, Multistart is most appropriate. A small numerical experiment shows that Maximin models have on average the most optima, of which the model locating an obnoxious linesegment has the most. Maximin models have few optima and are thus not very hard to solve. From the Minisum models, the models that have the most optima are models that take wind into account. In general can be said that the generic models have less optima than the weighted versions. Models that are measured with the rectilinear norm do have more solutions than the same models measured with the Euclidean norm. This can be explained for the maximin models in the numerical example because the shape of the norm coincides with a bound of the feasible area, so not all solutions are different optima. The difference found in number of optima of the Maxisum and Minisum can not be explained by this phenomenon

    THE RELEVANCE OF INFORMATION COMMUNICATION TECHNOLOGIES (ICTs) IN AGROFORESTRY PRACTICES

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    Heathcote (2000) posited that “Within half a century, computers and information technology have changed the world andaffected millions of lives in ways that no one could have foreseen”. The great impacts, contributions to knowledge,importance and economic achievements that have emerged from the fields of computer science (information science) andelectronic engineering, in the 21st century, are revolutionary and mind boggling (Bamgbade,2011). This paper explores theextent to which ICT applications have improved agro-forestry practices and discussed areas of application such as forestryand environmental management, species identification, research publication, ICT in agroforestry education, plant pathologystudies, wood anatomy, biometrics, Data management, modeling, analysis and miningKeywords: ICTs, Agroforestry, Impact, Management, Computers, Practices and Applications

    Groundwater Management Optimization and Saltwater Intrusion Mitigation under Uncertainty

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    Groundwater is valuable to supply fresh water to the public, industries, agriculture, etc. However, excessive pumping has caused groundwater storage degradation, water quality deterioration and saltwater intrusion problems. Reliable groundwater flow and solute transport modeling is needed for sustainable groundwater management and aquifer remediation design. However, challenges exist because of highly complex subsurface environments, computationally intensive groundwater models as well as inevitable uncertainties. The first research goal is to explore conjunctive use of feasible hydraulic control approaches for groundwater management and aquifer remediation. Water budget analysis is conducted to understand how groundwater withdrawals affect water levels. A mixed integer multi-objective optimization model is constructed to derive optimal freshwater pumping strategies and investigate how to promote the optimality through regulating pumping locations. A solute transport model for the Baton Rouge multi-aquifer system is developed to assess saltwater encroachment under current condition. Potential saltwater scavenging approach is proposed to mitigate the salinization issue in the Baton Rouge area. The second research goal aims to develop robust surrogate-assisted simulation-optimization modeling methods for saltwater intrusion mitigation. Machine learning based surrogate models (response surface regression model, artificial neural network and support vector machine) were developed to replace a complex high-fidelity solute transport model for predicting saltwater intrusion. Two different methods including Bayesian model averaging and Bayesian set pair analysis are used to construct ensemble surrogates and quantify model prediction uncertainties. Besides. different optimization models that incorporate multiple ensemble surrogates are formulated to obtain optimal saltwater scavenging strategies. Chance-constrained programming is used to account for model selection uncertainty in probabilistic nonlinear concentration constraints. The results show that conjunctive use of hydraulic control approaches would be effective to mitigate saltwater intrusion but needs decades. Machine learning based ensemble surrogates can build accurate models with high computing efficiency, and hence save great efforts in groundwater remediation design. Including model selection uncertainty through multimodel inference and model averaging provides more reliable remediation strategies compared with the single-surrogate assisted approach

    Happiness—Concept, Measurement and Promotion

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    This open access book defines happiness intuitively and explores several common conceptual mistakes with regard to happiness. It then moves on to address topical issues including, but not limited to, whether money can buy you happiness, why happiness is ultimately the only thing of intrinsic value, and the various factors important for happiness. It also presents a more reliable and interpersonally comparable method for measuring happiness and discusses twelve factors, from A to L, that are crucial for individual happiness: attitude, balance, confidence, dignity, engagement, family/friends, gratitude, health, ideals, joyfulness, kindness and love. Further, it examines important public policy considerations, taking into account recent advances in economics, the environmental sciences, and happiness studies. Novel issues discussed include: an environmentally responsible happy nation index to supplement GDP, the East Asian happiness gap, a case for stimulating pleasure centres of the brain, and an argument for higher public spending

    A Review of Geophysical Modeling Based on Particle Swarm Optimization

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    This paper reviews the application of the algorithm particle swarm optimization (PSO) to perform stochastic inverse modeling of geophysical data. The main features of PSO are summarized, and the most important contributions in several geophysical felds are analyzed. The aim is to indicate the fundamental steps of the evolution of PSO methodologies that have been adopted to model the Earth’s subsurface and then to undertake a critical evaluation of their benefts and limitations. Original works have been selected from the existing geophysical literature to illustrate successful PSO applied to the interpretation of electromagnetic (magnetotelluric and time-domain) data, gravimetric and magnetic data, self-potential, direct current and seismic data. These case studies are critically described and compared. In addition, joint optimization of multiple geophysical data sets by means of multi-objective PSO is presented to highlight the advantage of using a single solver that deploys Pareto optimality to handle diferent data sets without conficting solutions. Finally, we propose best practices for the implementation of a customized algorithm from scratch to perform stochastic inverse modeling of any kind of geophysical data sets for the beneft of PSO practitioners or inexperienced researchers

    Happiness—Concept, Measurement and Promotion

    Get PDF
    This open access book defines happiness intuitively and explores several common conceptual mistakes with regard to happiness. It then moves on to address topical issues including, but not limited to, whether money can buy you happiness, why happiness is ultimately the only thing of intrinsic value, and the various factors important for happiness. It also presents a more reliable and interpersonally comparable method for measuring happiness and discusses twelve factors, from A to L, that are crucial for individual happiness: attitude, balance, confidence, dignity, engagement, family/friends, gratitude, health, ideals, joyfulness, kindness and love. Further, it examines important public policy considerations, taking into account recent advances in economics, the environmental sciences, and happiness studies. Novel issues discussed include: an environmentally responsible happy nation index to supplement GDP, the East Asian happiness gap, a case for stimulating pleasure centres of the brain, and an argument for higher public spending
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