Search results for "optimization"

showing 10 items of 2824 documents

Memetic algorithms and memetic computing optimization: A literature review

2012

Abstract Memetic computing is a subject in computer science which considers complex structures such as the combination of simple agents and memes, whose evolutionary interactions lead to intelligent complexes capable of problem-solving. The founding cornerstone of this subject has been the concept of memetic algorithms, that is a class of optimization algorithms whose structure is characterized by an evolutionary framework and a list of local search components. This article presents a broad literature review on this subject focused on optimization problems. Several classes of optimization problems, such as discrete, continuous, constrained, multi-objective and characterized by uncertainties…

Structure (mathematical logic)Class (computer programming)Optimization problemGeneral Computer ScienceComputer sciencebusiness.industryGeneral MathematicsEvolutionary algorithmSubject (documents)Simple (abstract algebra)Memetic algorithmLocal search (optimization)Artificial intelligencebusinessSwarm and Evolutionary Computation
researchProduct

A multi objective genetic algorithm for the facility layout problem based upon slicing structure encoding

2012

This paper proposes a new multi objective genetic algorithm (MOGA) for solving unequal area facility layout problems (UA-FLPs). The genetic algorithm suggested is based upon the slicing structure where the relative locations of the facilities on the floor are represented by a location matrix encoded in two chromosomes. A block layout is constructed by partitioning the floor into a set of rectangular blocks using guillotine cuts satisfying the areas requirements of the departments. The procedure takes into account four objective functions (material handling costs, aspect ratio, closeness and distance requests) by means of a Pareto based evolutionary approach. The main advantage of the propos…

Structure (mathematical logic)Mathematical optimizationClosenessGeneral EngineeringPareto principleSlicingComputer Science ApplicationsSet (abstract data type)Artificial IntelligenceEncoding (memory)Genetic algorithmMulti Objective Genetic Algorithm Facility Layout ProblemSlicing StructureMathematicsBlock (data storage)Expert Systems with Applications
researchProduct

A geometrical approach for inverting display color-characterization models

2008

— Some display color-characterization models are not easily inverted. This work proposes ways to build geometrical inverse models given any forward color-characterization model. The main contribution is to propose and analyze several methods to optimize the 3-D geometrical structure of an inverse color-characterization model directly based on the forward model. Both the amount of data and their distribution in color space is especially focused on. Several optimization criteria, related either to an evaluation data set or to the geometrical structure itself, are considered. A practical case with several display devices, combining the different methods proposed in the article, are considered …

Structure (mathematical logic)Mathematical optimizationComputer scienceInverseColor spaceAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsDisplay deviceCharacterization (materials science)Set (abstract data type)Distribution (mathematics)Electrical and Electronic EngineeringAlgorithmInterpolationJournal of the Society for Information Display
researchProduct

Implementation aspects of interactive multiobjective optimization for modeling environments: The case of GAMS-NIMBUS

2014

Abstract. Interactive multiobjective optimization methods have provided promising results in the literature but still their implementations are rare. Here we introduce a core structure of interactive methods to enable their convenient implementation. We also demonstrate how this core structure can be applied when implementing an interactive method using a modeling environment. Many modeling environments contain tools for single objective optimization but not for interactive multiobjective optimization. Furthermore, as a concrete example, we present GAMS-NIMBUS Tool which is an implementation of the classification-based NIMBUS method for the GAMS modeling environment. So far, interactive met…

Structure (mathematical logic)Mathematical optimizationControl and OptimizationModeling languageComputer sciencepareto optimalityApplied Mathematicsinteractive methodsMultiple objective programmingMulti-objective optimizationComputational MathematicsMultiobjective optimization problemSingle objectivemultiple objective programmingNIMBUS methodImplementationmodeling languages
researchProduct

Large‐scale set partitioning problems: Some real‐world instances hide a beneficial structure

2006

In this paper we consider large‐scale set partitioning problems. Our main purpose is to show that real‐world set partitioning problems originating from the container‐trucking industry are easier to tackle in respect to general ones. We show such different behavior through computational experiments: in particular, we have applied both a heuristic algorithm and some exact solution approaches to real‐world instances as well as to benchmark instances from Beasley OR‐library. Moreover, in order to gain an insight into the structure of the real‐world instances, we have performed and evaluated various instance perturbations. Didelės matematinės aibės dalijimo problemų sprendimas, nagrinėjant reali…

Structure (mathematical logic)Mathematical optimizationLagrangian relaxationHF5001-6182real-world instancesEconomic growth development planningScale (descriptive set theory)set partitioningSet (abstract data type)symbols.namesakecontainer-trucking industryinstance perturbationsOR-libraryLagrangian relaxationHD72-88Benchmark (computing)symbolsBusinessFinanceMathematicsTechnological and Economic Development of Economy
researchProduct

Black-Box solvers in combinatorial optimization

2015

Black box optimizers have a long tradition in the field of operations research. These procedures treat the objective function evaluation as a black box and therefore do not take advantage of its specific structure. Black-box optimization refers to the process in which there is a complete separation between the evaluation of the objective function —and perhaps other functions used to enforce constraints— and the solution procedure. The challenge of optimizing black boxes is to develop methods that can produce outcomes of reasonable quality without taking advantage of problem structure and employing a computational effort that is adequate for the context.

Structure (mathematical logic)Mathematical optimizationLinear programmingProcess (engineering)Computer scienceBlack boxCombinatorial optimizationContext (language use)Multi-objective optimizationField (computer science)2015 International Conference on Industrial Engineering and Systems Management (IESM)
researchProduct

A multi-objective approach to facility layout problem by genetic search algorithm and Electre method

2006

Abstract Classical approaches to layout design problem tend to maximise the efficiency of layout, measured by the handling cost related to the interdepartmental flow and to the distance among the departments. However, the actual problem involves several conflicting objectives hence requiring a multi-objective formulation. Multi-objective approaches, recently proposed, in most cases lead to the maximisation of a weighted sum of score functions. The poor practicability of such an approach is due to the difficulty of normalising these functions and of quantifying the weights. In this paper, this difficulty is overcome by approaching the problem in two subsequent steps: in the first step, the P…

Structure (mathematical logic)Mathematical optimizationlayoutPage layoutGeneral MathematicsSolution setelectrecomputer.software_genreIndustrial and Manufacturing EngineeringComputer Science Applicationsmulti-objectiveControl and Systems EngineeringObjective approachGenetic algorithmSettore ING-IND/17 - Impianti Industriali Meccanicigenetic algorithmAdjacency listELECTREcomputerSoftwareSelection (genetic algorithm)Mathematics
researchProduct

A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms

2014

The file attached to this record is the author's final peer reviewed version. The publisher's final version can be found by following the DOI link. The ensemble structure is a computational intelligence supervised strategy consisting of a pool of multiple operators that compete among each other for being selected, and an adaptation mechanism that tends to reward the most successful operators. In this paper we extend the idea of the ensemble to multiple local search logics. In a memetic fashion, the search structure of an ensemble framework cooperatively/competitively optimizes the problem jointly with a pool of diverse local search algorithms. In this way, the algorithm progressively adapts…

Structure (mathematical logic)Theoretical computer sciencebusiness.industryComputer scienceMeta-heuristicsComputational intelligenceAdaptive algorithmsDifferential evolutionLocal search (optimization)OptimisationDifferential evolutionAdaptation (computer science)businessGlobal optimizationAlgorithmMetaheuristicEnsembleMemetic ComputingCurse of dimensionality
researchProduct

A Unified Approach to Portfolio Optimization with Linear Transaction Costs

2004

In this paper we study the continuous time optimal portfolio selection problem for an investor with a finite horizon who maximizes expected utility of terminal wealth and faces transaction costs in the capital market. It is well known that, depending on a particular structure of transaction costs, such a problem is formulated and solved within either stochastic singular control or stochastic impulse control framework. In this paper we propose a unified framework, which generalizes the contemporary approaches and is capable to deal with any problem where transaction costs are a linear/piecewise-linear function of the volume of trade. We also discuss some methods for solving numerically the p…

Structure (mathematical logic)Transaction costMathematical optimizationComputer sciencejel:C63General Mathematicsjel:C61Function (mathematics)Management Science and Operations ResearchSingular controljel:G11Merton's portfolio problemEconomicsPortfolioPortfolio optimizationportfolio choice transaction costs stochastic singular control stochastic impulse control computational methodsSoftwareExpected utility hypothesisSSRN Electronic Journal
researchProduct

Subdifferential and conjugate calculus of integral functions with and without qualification conditions

2023

We characterize the subdifferential and the Fenchel conjugate of convex integral functions by means of respectively the approximate subdifferential and the conjugate of the associated convex normal integrands. The results are stated in Suslin locally convex spaces, and do not require continuity-type qualification conditions on the functions, nor special topological or algebraic structures on the index set. Consequently, when confined to separable Banach spaces, the characterizations of such a subdifferential are obtained using only the exact subdifferential of the given integrand but at nearby points. We also provide some simplifications of our formulas when additional continuity conditions…

Subdifferentialsconvex normal integrandsConvex normal integrandsSuslin spacessub-differentialsSuslin spaces. Mathematics Subject Classi…cation (2010): 26B0526J25[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]49H05Integral functions and functionals
researchProduct