Search results for "Mathematical optimization"
showing 10 items of 1300 documents
A novel identification method for generalized T-S fuzzy systems
2012
Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/893807 In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulation results show the effectiveness of the proposed algorithm
On a stochastic disease model with vaccination
2006
We propose a stochastic disease model where vaccination is included and such that the immunity isn’t permanent. The existence, uniqueness and positivity of the solution and the stability of disease free equilibrium is studied. The numerical simulation is done.
Different Methods of Artificial Intelligence Used for Optimization the Turning Process
2015
In this paper, we realize a comparative study between some heuristics methods applied in turning operation in order to find optimal cutting parameters. We consider five different constraints aimed to achieve minimum total cost of machining. We have chosen the Simulated Annealing (SA) – a local search method, and Weighted-Sum Genetic Algorithm (WSGA) – a non-Pareto approach of a multi-objective optimization algorithm, based on a weighted aggregation of objectives. The aggregation may be with fixed weights or with random (variable) weights. The simulations showed that, even if it produces better results than the SA, WSGA with fixed weights, does not lead to optimum results, highlighting in th…
Dual Inequalities for Stabilized Column Generation Revisited
2014
Column generation (CG) models have several advantages over compact formulations: they provide better linear program bounds, may eliminate symmetry, and can hide nonlinearities in their subproblems. However, users also encounter drawbacks in the form of slow convergence, also known as the tailing-off effect, and the oscillation of the dual variables. Among different alternatives for stabilizing the CG process, Ben Amor et al. [Ben Amor H, Desrosiers J, Valério de Carvalho JM (2006) Dual-optimal inequalities for stabilized column generation. Oper. Res. 54(3):454–463] suggest the use of dual-optimal inequalities (DOIs) in the context of cutting stock and bin packing problems. We generalize th…
A Modified Tabu Thresholding Approach for the Generalised Restricted Vertex Colouring Problem
1996
We present a modification of the Tabu Thresholding (TT) approach and apply it to the solution of the generalised restricted vertex colouring problem. Both the bounded and unbounded cases are treated. In our algorithms, the basic TT elements are supplemented with an evaluation function that depends on the best solution obtained so far, together with a mechanism which reinforces the aggressive search in the improving phase, and new diversification strategies which depend on the state of the search. The procedure is illustrated through the solution of the problem of minimising the number of workers in a heterogeneous workforce.
A graph colouring model for assigning a heterogeneous workforce to a given schedule
1996
Abstract We analyze a heterogeneous workforce assignment problem in which the minimum number of workers required to carry out a machine load plan is calculated. The problem is formulated as a restricted vertex colouring problem and a branch and bound algorithm is presented. The special characteristics of the graph to be coloured allow an efficient implementation of the branch and bound. Computational results show that the algorithm can solve problems of 50 activities, 5, 10 and 15 machines and between 2 to 15 different types of workers in just a few seconds.
On solving single elevator-like problems using a learning automata-based paradigm
2020
This paper concentrates on a host of problems with characteristics similar to those that are related to moving elevators within a building. These are referred to as Elevator-like problems (ELPs), and their common phenomena will be expanded on in the body of the paper. We shall resolve ELPs using a subfield of AI, namely the field of learning automata (LA). Rather than working with the well-established mathematical formulations of the field, our intention is to use these tools to tackle ELPs, and in particular, those that deal with single “elevators” moving between “floors”. ELPs have not been tackled before using AI. In a simplified domain, the ELP involves the problem of optimizing the sch…
Agent assisted interactive algorithm for computationally demanding multiobjective optimization problems
2015
Abstract We generalize the applicability of interactive methods for solving computationally demanding, that is, time-consuming, multiobjective optimization problems. For this purpose we propose a new agent assisted interactive algorithm. It employs a computationally inexpensive surrogate problem and four different agents that intelligently update the surrogate based on the preferences specified by a decision maker. In this way, we decrease the waiting times imposed on the decision maker during the interactive solution process and at the same time decrease the amount of preference information expected from the decision maker. The agent assisted algorithm is not specific to any interactive me…
Fast nonstationary preconditioned iterative methods for ill-posed problems, with application to image deblurring
2013
We introduce a new iterative scheme for solving linear ill-posed problems, similar to nonstationary iterated Tikhonov regularization, but with an approximation of the underlying operator to be used for the Tikhonov equations. For image deblurring problems, such an approximation can be a discrete deconvolution that operates entirely in the Fourier domain. We provide a theoretical analysis of the new scheme, using regularization parameters that are chosen by a certain adaptive strategy. The numerical performance of this method turns out to be superior to state-of-the-art iterative methods, including the conjugate gradient iteration for the normal equation, with and without additional precondi…
Optimization of conducting structures by using the homogenization method
2002
Approximation and numerical realization of a class of optimization problems with control variables represented by coefficients of linear elliptic state equations is considered. Convergence analysis of well-posed problems is performed by using one- and two-level approximation strategies. The latter is utilized in an optimization layout problem for two conductive constituents, for which the necessary steps to transfer the well-posed problem into a computational form are described and some numerical experiments are given.