• To this end, algorithms for self-optimization of network parameters are an essential tool to increase network efficiency and reduce capital and operational expense. (kth.se)
  • We then show how to effectively model RET optimization in LCBs and demonstrate that our algorithms can produce optimal tilt update policies using much fewer data samples than naive or existing rule-based learning algorithms. (kth.se)
  • For analyzing and solving these interesting and challenging problems, typically techniques from network and combinatorial optimization and efficient algorithms must be provided. (dagstuhl.de)
  • My research helps to understand important algorithms for solving linear programming problems, including the Simplex method, Internal Point methods, and Cutting Plane methods. (cwi.nl)
  • This allows to extend algorithms for smooth unconstrained optimization and apply them to nonsmooth (possibly constrained) problems. (springer.com)
  • Small and often disconnected feasible patches, high underling dimensionality of the variable space and computationally expensive assessment of constraints pose significant challenges to population based stochastic optimization algorithms. (edu.au)
  • This project will focus on design of computationally efficient optimization algorithms to solve such classes of problems e.g. (edu.au)
  • Results obtained by the proposed method on a set of well known benchmarks are compared to the results obtained by the standard line search method, genetic algorithms and differential evolution. (sciweavers.org)
  • It is one of the most robust global optimization algorithms, although it is also one of the slowest. (copasi.org)
  • We develop and analyze several second order algorithms for computing an approximately optimal solution (regularization) path of a parameterized convex optimization problem with smooth Hessian. (berkeley.edu)
  • To design and implement optimization algorithms, several methods are used that bring superior performance. (theiet.org)
  • To overcome these limitations and to solve efficiently large scale combinatorial and highly nonlinear optimization problems, more flexible and adaptable algorithms are necessary. (theiet.org)
  • The discipline of nature-inspired optimization algorithms is a major field of computational intelligence, soft computing and optimization. (theiet.org)
  • Metaheuristic search algorithms with population-based frameworks are capable of handling optimization in high-dimensional real-world problems for several domains including imaging, IoT, smart manufacturing, and healthcare. (theiet.org)
  • Gradient descent, the multiplicative weights update method, the Frank-Wolfe gradient descent algorithm. (warwick.ac.uk)
  • The simulation results showed the reliability of the forecasting model as well as the comparison between the accuracy of optimization methods to choose the most appropriate algorithm that ensures optimal scheduling of the microgrid generators in the two proposed energy management scenarios allowing to prove the interest of the bi-directionality between the microgrid and the main grid. (easychair.org)
  • In 1947, George Dantzig invented the simplex algorithm, which is still widely used around the world for optimization processes: from optimizing compound feeds to aircraft movements. (cwi.nl)
  • The purpose of this paper is to discuss the application of a hybrid fuzzy reasoning and genetic algorithm method to graph optimization. (actapress.com)
  • Simulated annealing is an optimization algorithm first proposed by Kirkpatrick et al. (copasi.org)
  • The simulated annealing optimization algorithm uses a similar concept: the objective function is considered a measure of the energy of the system and this is maintained constant for a certain number of iterations (a temperature cycle). (copasi.org)
  • A deterministic global optimization algorithm based on augmented Lagrangian is proposed for solving the nonlinear programming with cone constraints, which is often encountered in technical design and operational research. (academicjournals.org)
  • Bone metastasis detection method based on improving golden jackal optimization using whale optimization algorithm. (bvsalud.org)
  • GJOW enhances the effectiveness of the golden jackal optimization (GJO) algorithm by integrating operators from the whale optimization algorithm (WOA). (bvsalud.org)
  • The aim is for students to learn the mathematical and algorithmic foundations underpinning optimization problems that are ubiquitous in applications in machine learning, data analysis and scientific computing. (warwick.ac.uk)
  • However, the resulting nonconvex optimization problems are still challenging, especially for the structured sparsity-inducing regularizers. (aaai.org)
  • Nonconvex Optimization and Its Applications , vol. 61, 1st edn. (esaim-cocv.org)
  • This paper introduces a modified version of the well known global optimization technique named line search method. (sciweavers.org)
  • The modified line search technique (MLS) is applied for some global optimization problems. (sciweavers.org)
  • Numerical results are obtained via different types of linearization of the nonlinearities and the use of mixed-integer linear solvers, and compared with state-of-the-art global optimization software. (kobv.de)
  • A.A. Aguiar, O.P. Ferreira and L.F. Prudente, Subgradient method with feasible inexact projections for constrained convex optimization problems. (esaim-cocv.org)
  • The central problem of optimization is minimization of functions. (wikipedia.org)
  • In this paper, we present new methods for black-box convex minimization. (optimization-online.org)
  • M. Raydan , The Barzilai and Borwein gradient method for the large scale unconstrained minimization problem, SIAM Journal of Optimization , 7 (1997) , 26-33. (aimsciences.org)
  • M. Abbas, M. AlShahrani, Q.H. Ansari, O.S. Iyiola and Y. Shehu, Iterative methods for solving proximal split minimization problems. (esaim-cocv.org)
  • Article: Roughness modelling and optimisation in EDM using response surface method for different work piece materials Journal: International Journal of Machining and Machinability of Materials (IJMMM) 2009 Vol.5 No.2/3 pp.321 - 346 Abstract: Influence of machining parameters, viz. (inderscience.com)
  • We address RET optimization in the Contextual Bandit (CB) setting, a powerful sequential decision-making framework that allows to efficiently model and solve the RET optimization problem. (kth.se)
  • Given a twice differentiable function f : R → R {\displaystyle f:\mathbb {R} \to \mathbb {R} } , we seek to solve the optimization problem min x ∈ R f ( x ) . {\displaystyle \min _{x\in \mathbb {R} }f(x). (wikipedia.org)
  • Newton's method attempts to solve this problem by constructing a sequence { x k } {\displaystyle \{x_{k}\}} from an initial guess (starting point) x 0 ∈ R {\displaystyle x_{0}\in \mathbb {R} } that converges towards a minimizer x ∗ {\displaystyle x_{*}} of f {\displaystyle f} by using a sequence of second-order Taylor approximations of f {\displaystyle f} around the iterates. (wikipedia.org)
  • Designers are often faced with the need to solve large scale, computationally expensive constrained optimization problems. (edu.au)
  • Specifically, we implement the Local Discontinuous Galerkin (LDG) Finite Element Method (FEM) to solve the resulting convection-diffusion Partial Differential Equation (PDE), and obtain error estimates for the LDG method. (ssrn.com)
  • This course focuses on the practical aspects of using convex optimization methods to solve these problems. (umich.edu)
  • To solve the state and corresponding adjoint equations we use the multimesh finite element method. (siam.org)
  • His scientific interests span from Bayesian inference (especially Monte Carlo methods), statistical modeling, machine learning to stochastic optimization. (cam.ac.uk)
  • At their core, many real-world problems involve optimisation problems that are complex and challenging, and they require rpincipled mathematical and algorithmic solutions. (warwick.ac.uk)
  • There are several interrelated aims of this module: (1) to expose students to optimisation methods that have found significant applications, (2) to develop a toolkit of mathematical methods that can be used to tackle real-world problems, and (3) to rigorously analyse these methods. (warwick.ac.uk)
  • Implement optimisation methods and apply them to real-world problems. (warwick.ac.uk)
  • The main topic of the seminar is algorithmic methods for analyzing and solving problems arising in railway optimization. (dagstuhl.de)
  • Many optimization problems can be represented as optimizing the labels of a graph so our methods should be widely applicable. (actapress.com)
  • In this paper, we propose a splitting method for solving nonconvex structured sparsity optimization problems. (aaai.org)
  • The bundle-level method and their certain variants are known to exhibit an optimal rate of convergence, i.e., ${\cal O}(1/\sqrt{t})$, and also excellent practical performance for solving general non-smooth convex programming (CP) problems. (optimization-online.org)
  • In this paper we analyze several new methods for solving optimization problems with the objective function formed as a sum of two convex terms: one is smooth and given by a black-box oracle, and another is general but simple and its structure is known. (optimization-online.org)
  • In the optimization problems matrix equations of the type Ax = b, with A sparse and badly conditioned, are accelerated using deflation techniques in addition to preconditioning. (tudelft.nl)
  • We have applied several iterative methods, preconditioners, and deflation types to the topology optimization problems. (tudelft.nl)
  • In this paper, a new manufacturing service composition scheme named as Multi-Batch Subtasks Parallel-Hybrid Execution Cloud Service Composition for Cloud Manufacturing (MBSPHE-CSCCM) is proposed, and such composition is one of the most difficult combination optimization problems with NP-hard complexity. (hindawi.com)
  • We study the performance of first- and second-order optimization methods for \(\ell _1\) -regularized sparse least-squares problems as the conditioning of the problem changes and the dimensions of the problem increase up to one trillion. (springer.com)
  • In order to address large scale problems there has been a resurgence in methods with computationally inexpensive iterations. (springer.com)
  • Convex optimization plays a central role in the numerical solution of many design and analysis problems in control theory. (umich.edu)
  • O.P. Ferreira, A robust semi-local convergence analysis of Newton's method for cone inclusion problems in Banach spaces under affine invariant majorant condition. (esaim-cocv.org)
  • We have witnessed an explosion of research activity around nature-inspired computing and bio-inspired optimization techniques, which can provide powerful tools for solving learning problems and data analysis in very large data sets. (theiet.org)
  • Both maximizing and minimizing are two categories of optimization problems. (theiet.org)
  • Optimization methods are applied to many problems in various fields to handle practical problems. (theiet.org)
  • difference and differential equations, · dynamic optimisation problems. (lu.se)
  • 2/4 course, · analyse dynamic optimisation problems using the theories and methods treated in the course, · apply the mathematical methods on economic problems. (lu.se)
  • The course deals with the mathematical methods used for analyzing dynamic problems in ordinary economic theory. (lu.se)
  • The usage of the mathematical methods is exemplied by a selection of economic problems. (lu.se)
  • The course deals with methods for solving dynamic optimization problems with and without stochasticity using open-loop and closed-loop solutions. (lu.se)
  • A novel method is presented and explored within the framework of Potts neural networks for solving optimization problems with a non-trivial topology, with the airline crew scheduling problem as a target application. (lu.se)
  • The method is explored on a set of synthetic dealt with in a straightforward way using ``stan- problems, which are generated to resemble two dard'' ANN energy functions similar to those en- real-world problems representing long and medi- countered in spin physics. (lu.se)
  • One of the areas in Structure Optimization is Topology Optimization, which is used for Additive Manufacturing purposes. (tudelft.nl)
  • In this thesis we explore Static and Dynamic Topology Optimization. (tudelft.nl)
  • T. Borrvall and J. Petersson, Topology optimization of fluids in Stokes flow , Int. J. Numer. (siam.org)
  • In this work, we apply a design exploration and optimization process, based upon a synergetic use of different timing analysis and optimization methods (for example, worst case, probabilistic, and model-checking) and tools, to compute the latency of the paths, and the corresponding latency differences. (sae.org)
  • The temperature, pH, and amount of extraction solution were selected for optimization experiment using response surface methodology. (hindawi.com)
  • This paper focuses on the design of a distributed energy management system for the optimal operation of the microgrid using linear and nonlinear optimization methods. (easychair.org)
  • Performance Profiling for the Modified Multiple Spectral Gradient Methods and Standard Multiple Spectral Gradient Method in terms of Number of Iterations. (aimsciences.org)
  • Using the deflation type RBM and eigenvectors, reductions by a factor of 1.60 and 1.75 in the total needed time for 150 optimization iterations were achieved for grid sizes 120x120x20 and 180x180x30, respectively. (tudelft.nl)
  • An Experimental versus Numerical Shape Optimization Method. (umd.edu)
  • This paper describes and compares an experimental and a numerical method for shape optimization of continuum structures. (umd.edu)
  • The paper demonstrates the importance of designer's interaction during the shape optimization process. (umd.edu)
  • The discussion is made taking shape optimization of a hole in a tall beam as an example. (umd.edu)
  • An important step in shape optimization with partial differential equation constraints is to adapt the geometry during each optimization iteration. (siam.org)
  • A. Bernland, E. Wadbro, and M. Berggren, Acoustic shape optimization using cut finite elements , Int. J. Numer. (siam.org)
  • In the last sixty years, numerical optimization has facilitated large advancements in this field. (tudelft.nl)
  • In calculus, Newton's method (also called Newton-Raphson) is an iterative method for finding the roots of a differentiable function F, which are solutions to the equation F (x) = 0. (wikipedia.org)
  • In order to show the global convergence of the conjugate gradient method with the unified formula of parameters, we define some property (say Property A). We prove the global convergence of the method with Property A. Next, we apply the unified formula to a scaled conjugate gradient method and show its global convergence property. (aimsciences.org)
  • By uniform optimality we mean that the first-order methods themselves do not require the input of any problem parameters, but can still achieve the best possible iteration complexity bounds. (optimization-online.org)
  • The spectral parameters satisfy the modified weak secant relations that inspired by the multistep approximation for solving large scale unconstrained optimization. (aimsciences.org)
  • Each temperature cycle takes $10 \cdot p \cdot \max(5\,*p,\,100)$ random steps, with $p$ being the number of optimization parameters. (copasi.org)
  • The numerical method is based on coupling of a finite element analysis and an optimization method. (umd.edu)
  • K. Bandara, T. Rüberg, and F. Cirak, Shape optimisation with multiresolution subdivision surfaces and immersed finite elements , Comput. (siam.org)
  • This issue contains six papers that were presented in preliminary form at the 5th Workshop on Algorithmic Methods and Models for Optimization of Railways (ATMOS 2005), held at Palma de Mallorca, Spain, October 7, 2005 in conjunction with ALGO 2005. (dagstuhl.de)
  • J. A. Ford and I. A. Moghrabi , Multi-step quasi-Newton methods for optimization, Journal of Computational and Applied Mathematics , 50 (1994) , 305-323. (aimsciences.org)
  • F. Brezzi, J.-L. Lions, and O. Pironneau, Analysis of a Chimera method , Comptes Rendus de l'Academie des Sciences Series I Mathematics, 332 (2001), pp. 655--660. (siam.org)
  • S. Adly and V.N. Huynh, Quasi-Newton methods for solving nonsmooth equations: generalized Dennis-Moré theorem and Broyden's update. (esaim-cocv.org)
  • S. Adly, H. Van Ngai and V.V. Nguyen, Newton's method for solving generalized equations: Kantorovich's and Smale's approaches. (esaim-cocv.org)
  • F.R. de Oliveira, O.P. Ferreira and G.N. Silva, Newton's method with feasible inexact projections for solving constrained generalized equations. (esaim-cocv.org)
  • A.L. Dontchev and R.T. Rockafellar, Convergence of inexact Newton methods for generalized equations. (esaim-cocv.org)
  • O. Ferreira and G. Silva, Local convergence analysis of Newton's method for solving strongly regular generalized equations. (esaim-cocv.org)
  • N. Josephy, Newton's method for generalized equations and the pies energy model, Ph.D. thesis, University of Wisconsin-Madison (1979). (esaim-cocv.org)
  • The course also covers solving linear systems of dierence and dierential equations using the eigenvalue methods and Guassian elimination. (lu.se)
  • Optimization results show that it is feasible to implement BMPs for non-point sources in each sub-watershed to meet reduction targets at a cost of $1.0 million. (usu.edu)
  • F.J. Aragon Artacho, A. Belyakov, A.L. Dontchev and M. Lopez, Local convergence of quasi-Newton methods under metric regularity. (esaim-cocv.org)
  • J.E. Dennis and J.J. Morée, Quasi-Newton methods, motivation and theory. (esaim-cocv.org)
  • J.E. Dennis and J.J. Morée, A characterization of superlinear convergence and its application to quasi-Newton methods. (esaim-cocv.org)
  • 1984~. Reverse phase HPLC method of analysis of TNT, RDX, HMX and 2,4-DNT in munitions waste water. (cdc.gov)
  • Optimisation of HPLC systems with different combinations of mobile phases for quantitative and qualitative analysis of small molecules. (lu.se)
  • So, optimization is nothing but making the best feasible decision. (theiet.org)
  • Biomechanical simulation employs kinematic and kinetic analyses and optimization techniques to reduce the large number of possible body motion patterns to a feasible number needed to perform a task. (cdc.gov)
  • Beside algorithmics and mathematical optimization the relevance of formal models and the influence of application aspects for the problem modelling are considered as well. (dagstuhl.de)
  • The proposed method alternates between a gradient step and an easily solvable proximal step, and thus enjoys low per-iteration computational complexity. (aaai.org)
  • D. C. Liu and J. Nocedal , On the limited memory BFGS method for large scale optimization, Mathematical Programming , 45 (1989) , 503-528. (aimsciences.org)
  • J. E. Dennis and H. Wolkowicz , Sizing and least change secant methods, SIAM Journal on Numerical Analysis , 30 (1993) , 1291-1313. (aimsciences.org)
  • M. Zhu , J. L. Nazareth and H. Wolkowicz , The quasi-Cauchy relation and diagonal updating, SIAM Journal on Optimization , 4 (1999) , 1192-1204. (aimsciences.org)
  • Energy management in the microgrid system is generally formulated as an optimization problem. (easychair.org)
  • train solves the optimization problem to obtain a model. (github.com)
  • Due to the intractability of the problem, modelers resort to numerical methods to obtain approximations of solutions to the problem. (ssrn.com)
  • The static problem concerns compliance optimization of a two-dimensional MBB-beam. (tudelft.nl)
  • The dynamic problem concerns eigenvalue optimization of a three-dimensional moving wafer stage that is used for laser-printing computer chips. (tudelft.nl)
  • The optimization formulation contains a shifted eigenvalue problem that is solved using model order reduction. (tudelft.nl)
  • To address the problem, a novel optimization method named as Improved Hybrid Differential Evolution and Teaching Based Optimization (IHDETBO) is proposed and introduced in detail. (hindawi.com)
  • With the advancement in computing techniques, optimization has become an important part of problem solving. (theiet.org)
  • A number of excellent articles appeared in the literature [ 2 - 8 ] that described strategies for the application of QbD principles to chromatographic method development. (ijpsonline.com)
  • This method weakly enforces continuity over the nonmatching mesh interfaces by using Nitsche and additional stability terms. (siam.org)
  • In this thesis, we study Remote Electrical Tilt (RET) optimization using learning-based methods. (kth.se)
  • With the results obtained in this thesis, we argue that a significant improvement for sample complexity and operational safety can be achieved while learning RET optimization policies in CBs, providing potential for real-world network deployment of learning-based RET policies. (kth.se)
  • Huiberts defended her PhD thesis 'Geometric aspects of linear programming: shadow paths, central paths, and a cutting plane method' at Utrecht University on 16 May. (cwi.nl)
  • As such, the main objective of this thesis is to develop a method for environmental building design optimization that is applicable in the design process. (uni-weimar.de)
  • The key concept proposed in this thesis is to combine LCA with parametric design, because it proved to have a high potential for design optimization. (uni-weimar.de)
  • In this thesis, it served as guideline for the development of the parametric method - Parametric Life Cycle Assessment (PLCA). (uni-weimar.de)
  • The focus of the work presented in this thesis has been on the optimization and development of DGE MRI in humans. (lu.se)
  • In these methods, the objective is to learn an optimal control policy, adjusting the vertical tilt of base station antennas to jointly maximize network coverage and capacity. (kth.se)
  • The main goal of this paper is to develop uniformly optimal first-order methods for large-scale convex programming (CP). (optimization-online.org)
  • Our numerical experiments show the order of accuracy of the LDG method and illustrate the optimal policies under various kinds of transaction costs. (ssrn.com)
  • In this paper, we take the strategy as a given and propose methods and tools that aid designers in finding the desired trade-offs between satisfaction of the latency constraints and efficient usage of the hardware resources. (sae.org)
  • Submodular functions, submodular minimisation via the allipsoid method and gradient descent. (warwick.ac.uk)
  • It is very important to generate a descent search direction independent of line searches in showing the global convergence of conjugate gradient methods. (aimsciences.org)
  • The method of Hager and Zhang (2005) satisfies the sufficient descent condition. (aimsciences.org)
  • The forward-backward splitting method (FBS) for minimizing a nonsmooth composite function can be interpreted as a (variable-metric) gradient method over a continuously differentiable function which we call forward-backward envelope (FBE). (springer.com)
  • Tseng, P.: On accelerated proximal gradient methods for convex-concave optimization. (springer.com)
  • Nesterov, Y.: Gradient methods for minimizing composite functions. (springer.com)
  • Y. H. Dai, Nonlinear conjugate gradient methods , in "Wiley Encyclopedia of Operations Research and Management Science" (eds. (aimsciences.org)
  • In this paper, we aim to propose some spectral gradient methods via variational technique under log-determinant norm. (aimsciences.org)
  • An executable code is developed to test the efficiency of the proposed method with spectral gradient method using standard weak secant relation as constraint. (aimsciences.org)
  • Performance Profiling for the Modified Multiple Spectral Gradient Methods and Standard Multiple Spectral Gradient Method in terms of Number of Function Calls. (aimsciences.org)
  • J. Barzilai and J. Borwein , Two-point step size gradient methods, IMA Journal of Numerical Analysis , 8 (1988) , 141-148. (aimsciences.org)
  • M.L. Goncalves and J.G. Melo, A Newton conditional gradient method for constrained nonlinear systems. (esaim-cocv.org)
  • If f is a strongly convex function with Lipschitz Hessian, then provided that x 0 {\displaystyle x_{0}} is close enough to x ∗ = arg ⁡ min f ( x ) {\displaystyle x_{*}=\arg \min f(x)} , the sequence x 0 , x 1 , x 2 , … {\displaystyle x_{0},x_{1},x_{2},\dots } generated by Newton's method will converge to the (necessarily unique) minimizer x ∗ {\displaystyle x_{*}} of f {\displaystyle f} quadratically fast. (wikipedia.org)
  • 1986. TNT, RDX, HMX, and 2,4-DNT in waste water and groundwater liquid chromatographic method first action. (cdc.gov)
  • Liquid chromatographic method - 986.22. (cdc.gov)
  • In the present study a QbD acquiescent method utilizing design of experiment and method operable design regions methodology was evaluated for optimization of chomatographic condition for separation of ten degradation products along with peaks of aspirin and lansoprazole. (ijpsonline.com)
  • D. Azé and C.C. Chou, On a Newton type iterative method for solving inclusions. (esaim-cocv.org)
  • Scheinberg, K., Tang, X.: Practical inexact proximal quasi-Newton method with global complexity analysis. (springer.com)
  • To obtain the shape derivatives we analyze both the strong formulation (Hadamard formulation) and weak formulation (method of mappings). (siam.org)
  • R. Cibulka, A. Dontchev and A. Kruger, Strong metric subregularity of mappings in variational analysis and optimization. (esaim-cocv.org)
  • The course has a technical focus, with special emphasize on "evolutionary optimization" and "machine learning (including deep learning)" techniques. (lu.se)
  • The processes, coupled with optimization steps aimed at reducing the number of software and hardware resources while satisfying the safety requirements, enable reduction of the system complexity and ease downstream testing/validation efforts. (sae.org)
  • Learn optimisation methods that are widely used in applications. (warwick.ac.uk)
  • Existing learning-based RET optimization methods, mainly rely on trial-and-error learning paradigms that inevitably degrade network performance during exploration phases, or may require an excessively large amount of samples to converge. (kth.se)
  • Convergence stopping criteria: the method stops when the change in the objective function has been smaller than this value in the last two temperature steps. (copasi.org)
  • Scientists have now developed methods of determining the traffic situation across a wide area, and have refined processes that enable traffic to be optimally channeled. (sciencedaily.com)
  • Faculty research in Berkeley IEOR specializes in stochastic processes, optimization, and supply chain management. (berkeley.edu)
  • Convex optimisation methods and their applications. (warwick.ac.uk)
  • Structure Optimization has been an important subject with many applications for centuries. (tudelft.nl)
  • It is also a useful resource for professionals in related fields, and for advanced students with an interest in optimization and IoT applications. (theiet.org)
  • Methods and Tools for End-to-End Latency Analysis and Optimization of a Dual-Processor Control Module," SAE Technical Paper 2012-01-0029, 2012, https://doi.org/10.4271/2012-01-0029 . (sae.org)
  • The research approach includes the analysis of the characteristics of LCA for buildings and the architectural design stages to identify the research gap, the establishment of a requirement catalogue, the development of a method based on a digital, parametric model, and an evaluation of the method. (uni-weimar.de)
  • J.F. Bonnans, Local analysis of Newton-type methods for variational inequalities and nonlinear programming. (esaim-cocv.org)
  • AOAC Official Methods of Analysis. (cdc.gov)
  • Biomechanical modeling is regarded as a deductive method for describing body motions and utilizes techniques of kinematic and kinetic analysis to describe motions undergone by the various body segments and the forces acting on their body parts. (cdc.gov)
  • This prevents mistakes but also speed up analysis since some optimizations can be used when assigning positions in bioassay sets. (lu.se)