Search results for " Computer Science"
showing 10 items of 3983 documents
Interactive Multiobjective Optimization of Superstructure SMB Processes
2009
We consider multiobjective optimization problems arising from superstructure formulation of Simulated Moving Bed (SMB) processes. SMBs are widely used in many industrial separations of chemical products and they are challenging from the optimization point of view. We employ efficient interactive multiobjec-tive optimization which enables considering several conflicting objectives simultaneously without unnecessary simplifications as have been done in previous studies. The interactive IND-NIMBUS software combined with the IPOPT optimizer is used to solve multiobjective SMB design problems. The promising results of solving a superstructure SMB optimization problem with four objectives demonst…
Using a TSP heuristic for routing order pickers in warehouses
2010
In this paper, we deal with the sequencing and routing problem of order pickers in conventional multi-parallel-aisle warehouse systems. For this NP-hard Steiner travelling salesman problem (TSP), exact algorithms only exist for warehouses with at most three cross aisles, while for other warehouse types literature provides a selection of dedicated construction heuristics. We evaluate to what extent reformulating and solving the problem as a classical TSP leads to performance improvements compared to existing dedicated heuristics. We report average savings in route distance of up to 47% when using the LKH (Lin-Kernighan-Helsgaun) TSP heuristic. Additionally, we examine if combining problem-sp…
A homography formulation to the 3pt plus a common direction relative pose problem
2014
International audience; In this paper we present an alternative formulation for the minimal solution to the 3pt plus a common direction relative pose prob-lem. Instead of the commonly used epipolar constraint we use the homog-raphy constraint to derive a novel formulation for the 3pt problem. This formulation allows the computation of the normal vector of the plane defined by the three input points without any additional computation in addition to the standard motion parameters of the camera. We show the working of the method on synthetic and real data sets and compare it to the standard 3pt method and the 5pt method for relative pose estima-tion. In addition we analyze the degenerate condi…
The multiple vehicle pickup and delivery problem with LIFO constraints
2015
Abstract This paper approaches a pickup and delivery problem with multiple vehicles in which LIFO conditions are imposed when performing loading and unloading operations and the route durations cannot exceed a given limit. We propose two mixed integer formulations of this problem and a heuristic procedure that uses tabu search in a multi-start framework. The first formulation is a compact one, that is, the number of variables and constraints is polynomial in the number of requests, while the second one contains an exponential number of constraints and is used as the basis of a branch-and-cut algorithm. The performances of the proposed solution methods are evaluated through an extensive comp…
A genetic algorithm for discrete tomography reconstruction
2007
The aim of this paper is the description of an experiment carried out to verify the robustness of two different approaches for the reconstruction of convex polyominoes in discrete tomography. This is a new field of research, because it differs from classic computerized tomography, and several problems are still open. In particular, the stability problem is tackled by using both a modified version of a known algorithm and a new genetic approach. The effect of both, instrumental and quantization noises has been considered too. © 2007 Springer Science+Business Media, LLC.
A Visualizable Test Problem Generator for Many-Objective Optimization
2022
Visualizing the search behavior of a series of points or populations in their native domain is critical in understanding biases and attractors in an optimization process. Distancebased many-objective optimization test problems have been developed to facilitate visualization of search behavior in a two-dimensional design space with arbitrarily many objective functions. Previous works have proposed a few commonly seen problem characteristics into this problem framework, such as the definition of disconnected Pareto sets and dominance resistant regions of the design space. The authors’ previous work has advanced this research further by providing a problem generator to automatically create use…
Efficient Pruning LMI Conditions for Branch-and-Prune Rank and Chirality-Constrained Estimation of the Dual Absolute Quadric
2014
International audience; We present a new globally optimal algorithm for self- calibrating a moving camera with constant parameters. Our method aims at estimating the Dual Absolute Quadric (DAQ) under the rank-3 and, optionally, camera centers chirality constraints. We employ the Branch-and-Prune paradigm and explore the space of only 5 parameters. Pruning in our method relies on solving Linear Matrix Inequality (LMI) feasibility and Generalized Eigenvalue (GEV) problems that solely depend upon the entries of the DAQ. These LMI and GEV problems are used to rule out branches in the search tree in which a quadric not satisfy- ing the rank and chirality conditions on camera centers is guarantee…
A two-slope achievement scalarizing function for interactive multiobjective optimization
2012
The use of achievement (scalarizing) functions in interactive multiobjective optimization methods is very popular, as indicated by the large number of algorithmic and applied scientific papers that use this approach. Key parameters in this approach are the reference point, which expresses desirable objective function values for the decision maker, and weights. The role of the weights can range from purely normalizing to fully preferential parameters that indicate the relative importance given by the decision maker to the achievement of each reference value. Technically, the influence of the weights in the solution generated by the achievement scalarizing function is different, depending on …
Efficient Redundancy Reduced Subgroup Discovery via Quadratic Programming
2012
Subgroup discovery is a task at the intersection of predictive and descriptive induction, aiming at identifying subgroups that have the most unusual statistical (distributional) characteristics with respect to a property of interest. Although a great deal of work has been devoted to the topic, one remaining problem concerns the redundancy of subgroup descriptions, which often effectively convey very similar information. In this paper, we propose a quadratic programming based approach to reduce the amount of redundancy in the subgroup rules. Experimental results on 12 datasets show that the resulting subgroups are in fact less redundant compared to standard methods. In addition, our experime…
Adjoint-based sampling methods for electromagnetic scattering
2010
In this paper we investigate the efficient realization of sampling methods based on solutions of certain adjoint problems. This adjoint approach does not require the explicit knowledge of the Green's function for the background medium, and allows us to sample for all points and all dipole directions simultaneously; thus, several limitations of standard sampling methods are relieved. A detailed derivation of the adjoint approach is presented for two electromagnetic model problems, but the framework can be applied to a much wider class of problems. We also discuss a relation of the adjoint sampling method to standard backprojection algorithms, and present numerical tests that illustrate the e…