Search results for "Multi-Objective Optimization"

showing 10 items of 192 documents

More is more? : Forest management allocation at different spatial scales to mitigate conflicts between ecosystem services

2017

Context: Multi-objective management can mitigate conflicts among land-use objectives. However, the effectiveness of a multi-objective solution depends on the spatial scale at which land-use is optimized. This is because the ecological variation within the planning region influences the potential for site-specific prioritization according to the different objectives. Objectives: We optimized the allocation of forest management strategies to maximize the joint production of two conflicting objectives, timber production and carbon storage, at increasing spatial scales. We examined the impacts of the extent of the planning region on the severity of the conflict, the potential for its mitigation…

0106 biological sciences010504 meteorology & atmospheric sciencesGeography Planning and DevelopmentForest management010603 evolutionary biology01 natural scienceskestävä metsätalousEcosystem servicesmetsätalousoptimointiProduction (economics)land-sparingFinland0105 earth and related environmental sciencesNature and Landscape ConservationSustainable developmentEcologybusiness.industryScale (chemistry)Environmental resource managementPareto principle15. Life on landcarbon storagelandscape extentpuuntuotantoekosysteemipalvelutmulti-objective optimizationhiilinieluttimber productionstrateginen suunnitteluSpatial ecologyEnvironmental scienceland-sharingLandscape ecologymetsänhoitobusiness
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Data-Based Forest Management with Uncertainties and Multiple Objectives

2016

In this paper, we present an approach of employing multiobjective optimization to support decision making in forest management planning. The planning is based on data representing so-called stands, each consisting of homogeneous parts of the forest, and simulations of how the trees grow in the stands under different treatment options. Forest planning concerns future decisions to be made that include uncertainty. We employ as objective functions both the expected values of incomes and biodiversity as well as the value at risk for both of these objectives. In addition, we minimize the risk level for both the income value and the biodiversity value. There is a tradeoff between the expected val…

0106 biological sciencesPareto optimalityDecision support systeminteractive multiobjective optimization010504 meteorology & atmospheric sciencesOperations researchComputer sciencemedia_common.quotation_subjectForest managementmetsäsuunnitteluPlan (drawing)01 natural sciencesMulti-objective optimizationepävarmuusPreferenceInterdependencemultiobjective optimizationValue (mathematics)Value at risk010606 plant biology & botany0105 earth and related environmental sciencesmedia_common
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Quantifying and resolving conservation conflicts in forest landscapes via multiobjective optimization

2017

Environmental planning for of the maintenance of different conservation objectives should take into account multiple contrasting criteria based on alternative uses of the landscape. We develop new concepts and approaches to describe and measure conflicts among conservation objectives and for resolving them via multiobjective optimization. To measure conflicts we introduce a compatibility index that quantifies how much targeting a certain conservation objective affects the capacity of the landscape for providing another objective. To resolve such conflicts we find compromise solutions defined in terms of minimax regret, i.e. minimizing the maximum percentage of deterioration among conservati…

0106 biological sciencesta113ecosystem managementenvironmental conflicts010504 meteorology & atmospheric sciencesComputer scienceEcologydecision support toolsEcological Modelingforestry010603 evolutionary biology01 natural sciencesMulti-objective optimizationbiodiversiteettimetsätalousympäristökonfliktitta1181lcsh:SD1-669.5lcsh:Forestrysystematic conservation planningEnvironmental planningland-use planning0105 earth and related environmental sciencesbiodiversitySilva Fennica
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A Pareto optimal design approach for simultaneous control of thinning and springback in stamping processes

2009

One of the most relevant research issues in automotive field is focused on the reduction of stamped parts weight also increasing their strength. In this way, a strong research effort is developed on high strength steels which are widely utilized and they require a proper springback control. Springback reduction in sheet metal forming is a typical goal to be pursued which is conflicting with thinning reduction for instance. Thus, such problems can be considered as multi-objective ones characterized by conflicting objectives. What is more, nowadays, a great interest would be focused on the availability of a cluster of possible optimal solutions instead of a single one, particularly in an indu…

0209 industrial biotechnologyEngineeringMathematical optimizationsheet metal stampingAutomotive industryComputational intelligence02 engineering and technologyresponse surface methodBlankMulti-objective optimization[SPI.MAT]Engineering Sciences [physics]/Materialsspringback020901 industrial engineering & automationGeneral Materials ScienceResponse surface methodologySettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazionebusiness.industrythinningStructural engineering[SPI.MECA]Engineering Sciences [physics]/Mechanics [physics.med-ph]Stamping021001 nanoscience & nanotechnologymulti-objective optimizationvisual_artvisual_art.visual_art_medium0210 nano-technologybusinessSheet metalReduction (mathematics)International Journal of Material Forming
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A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms

2017

Evolutionary algorithms are widely used for solving multiobjective optimization problems but are often criticized because of a large number of function evaluations needed. Approximations, especially function approximations, also referred to as surrogates or metamodels are commonly used in the literature to reduce the computation time. This paper presents a survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems. Several algorithms are discussed based on what kind of an approximation such as problem, function or fitness approximation they use. Most emphasis is given to function approxim…

0209 industrial biotechnologyMathematical optimizationComputer scienceComputationEvolutionary algorithmComputational intelligence02 engineering and technologyMulti-objective optimizationTheoretical Computer Science020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringmulticriteria optimizationsurrogateresponse surface approximationcomputational costmetamodelFitness approximationpareto optimalitypareto-tehokkuusFunction (mathematics)monitavoiteoptimointiFunction approximationkoneoppiminen020201 artificial intelligence & image processingGeometry and TopologySoftware
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Iterated greedy with variable neighborhood search for a multiobjective waste collection problem

2020

Abstract In the last few years, the application of decision making to logistic problems has become crucial for public and private organizations. Efficient decisions clearly contribute to improve operational aspects such as cost reduction or service improvement. The particular case of waste collection service considered in this paper involves a set of economic, labor and environmental issues that translate into difficult operational problems. They pose a challenge to nowadays optimization technologies since they have multiple constraints and multiple objectives that may be in conflict. We therefore need to resort to multiobjective approaches to model and solve this problem, providing efficie…

0209 industrial biotechnologyService (systems architecture)Mathematical optimizationComputer sciencemedia_common.quotation_subjectGeneral EngineeringWaste collection02 engineering and technologyMulti-objective optimizationComputer Science ApplicationsSet (abstract data type)020901 industrial engineering & automationArtificial Intelligence0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingIterated greedyFunction (engineering)Variable neighborhood searchmedia_commonExpert Systems with Applications
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DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization

2021

Interactive multiobjective optimization methods incorporate preferences from a human decision maker in the optimization process iteratively. This allows the decision maker to focus on a subset of solutions, learn about the underlying trade-offs among the conflicting objective functions in the problem and adjust preferences during the solution process. Incorporating preference information allows computing only solutions that are interesting to the decision maker, decreasing computation time significantly. Thus, interactive methods have many strengths making them viable for various applications. However, there is a lack of existing software frameworks to apply and experiment with interactive …

0209 industrial biotechnologylineaarinen optimointiPareto optimizationGeneral Computer Sciencemulti-criteria decision makingComputer sciencepäätöksentekoevoluutiolaskenta02 engineering and technologyData-driven multiobjective optimizationcomputer.software_genrenonlinear optimizationMulti-objective optimizationData modelingopen source softwareavoin lähdekoodi020901 industrial engineering & automationSoftwareoptimointi0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceUse casecomputer.programming_languageGraphical user interfacepareto-tehokkuusbusiness.industryGeneral Engineeringinteractive methodsModular designPython (programming language)monitavoiteoptimointiTK1-9971Software frameworkdata-driven multiobjective optimizationevolutionary computation020201 artificial intelligence & image processingElectrical engineering. Electronics. Nuclear engineeringbusinessSoftware engineeringcomputerIEEE Access
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DESDEO : An Open Framework for Interactive Multiobjective Optimization

2018

We introduce a framework for interactive multiobjective optimization methods called DESDEO released under an open source license. With the framework, we want to make interactive methods easily accessible to be applied in solving real-world problems. The framework follows an object-oriented software design paradigm, where functionalities have been divided to modular, self-contained components. The framework contains implementations of some interactive methods, but also components which can be utilized to implement more interactive methods and, thus, increase the applicability of the framework. To demonstrate how the framework can be used, we consider an example problem where the pollution of…

021103 operations researchbusiness.industryComputer scienceDistributed computing0211 other engineering and technologies02 engineering and technologyModular designOpen frameworkMulti-objective optimizationmonitavoiteoptimointiOpen source licenseavoin lähdekoodioptimointiDESDEO0202 electrical engineering electronic engineering information engineeringSoftware design020201 artificial intelligence & image processingmultiobjective optimizationongelmanratkaisubusinessImplementationoptimization
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Integrating risk management tools for regional forest planning: an interactive multiobjective value-at-risk approach

2018

In this paper, we present an approach employing multiobjective optimization to support decision making in forest management planning under risk. The primary objectives are biodiversity and timber cash flow, evaluated from two perspectives: the expected value and the value-at-risk (VaR). In addition, the risk level for both the timber cash flow and biodiversity values are included as objectives. With our approach, we highlight the trade-off between the expected value and the VaR, as well as between the VaRs of the two objectives of interest. We employ an interactive method in which a decision maker iteratively provides preference information to find the most preferred management plan and le…

040101 forestryForest planningGlobal and Planetary Change010504 meteorology & atmospheric sciencesEcologyComputer scienceForest managementBiodiversityForestryRisk management tools04 agricultural and veterinary sciences01 natural sciencesMulti-objective optimization0401 agriculture forestry and fisheriesForest management planningEnvironmental planningValue at risk0105 earth and related environmental sciencesCanadian Journal of Forest Research
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An Interactive Framework for Offline Data-Driven Multiobjective Optimization

2020

We propose a framework for solving offline data-driven multiobjective optimization problems in an interactive manner. No new data becomes available when solving offline problems. We fit surrogate models to the data to enable optimization, which introduces uncertainty. The framework incorporates preference information from a decision maker in two aspects to direct the solution process. Firstly, the decision maker can guide the optimization by providing preferences for objectives. Secondly, the framework features a novel technique for the decision maker to also express preferences related to maximum acceptable uncertainty in the solutions as preferred ranges of uncertainty. In this way, the d…

050101 languages & linguisticsDecision support systemMathematical optimizationOptimization problemdecision supportComputer scienceEvolutionary algorithmGaussian processespäätöksentukijärjestelmät02 engineering and technologyMulti-objective optimizationdecision makingData-driven0202 electrical engineering electronic engineering information engineeringmetamodelling0501 psychology and cognitive sciencessurrogateInteractive visualization05 social sciencesgaussiset prosessitmonitavoiteoptimointiMetamodelingKriging020201 artificial intelligence & image processingdecomposition-based MOEAkriging-menetelmäCognitive load
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