Estimation of concentration-dependent diffusion coefficient in drying process from the space-averaged concentration versus time with experimental data
- Authors: Loulou, T. , Adhikari, Benu , Lecomte, D.
- Date: 2006
- Type: Text , Journal article
- Relation: Chemical Engineering Science Vol. 61, no. 22 (2006), p. 7185-7198
- Full Text: false
- Reviewed:
- Description: The estimation of a concentration-dependent diffusion coefficient in a drying process is known as an inverse coefficient problem. The solution is sought wherein the space-average concentration is known as function of time (mass loss monitoring). The problem is stated as the minimization of a functional and gradient-based algorithms are used to solve it. Many numerical and experimental examples that demonstrate the effectiveness of the proposed approach are presented. Thin slab drying was carried out in an isothermal drying chamber built in our laboratory. The diffusion coefficients of fructose obtained with the present method are compared with existing literature results. (c) 2006 Elsevier Ltd. All rights reserved.
An algorithm for minimizing clustering functions
- Authors: Bagirov, Adil , Ugon, Julien
- Date: 2005
- Type: Text , Journal article
- Relation: Optimization Vol. 54, no. 4-5 (Aug-Oct 2005), p. 351-368
- Full Text:
- Reviewed:
- Description: The problem of cluster analysis is formulated as a problem of nonsmooth, nonconvex optimization. An algorithm for solving the latter optimization problem is developed which allows one to significantly reduce the computational efforts. This algorithm is based on the so-called discrete gradient method. Results of numerical experiments are presented which demonstrate the effectiveness of the proposed algorithm.
- Description: C1
- Description: 2003001266
A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems
- Authors: Bagirov, Adil , Yearwood, John
- Date: 2006
- Type: Text , Journal article
- Relation: European Journal of Operational Research Vol. 170, no. 2 (2006), p. 578-596
- Full Text: false
- Reviewed:
- Description: The minimum sum-of-squares clustering problem is formulated as a problem of nonsmooth, nonconvex optimization, and an algorithm for solving the former problem based on nonsmooth optimization techniques is developed. The issue of applying this algorithm to large data sets is discussed. Results of numerical experiments have been presented which demonstrate the effectiveness of the proposed algorithm. © 2004 Elsevier B.V. All rights reserved.
- Description: C1
- Description: 2003001520
Piecewise partially separable functions and a derivative-free algorithm for large scale nonsmooth optimization
- Authors: Bagirov, Adil , Ugon, Julien
- Date: 2006
- Type: Text , Journal article
- Relation: Journal of Global Optimization Vol. 35, no. 2 (Jun 2006), p. 163-195
- Full Text:
- Reviewed:
- Description: This paper introduces the notion of piecewise partially separable functions and studies their properties. We also consider some of many applications of these functions. Finally, we consider the problem of minimizing of piecewise partially separable functions and develop an algorithm for its solution. This algorithm exploits the structure of such functions. We present the results of preliminary numerical experiments.
- Description: 2003001532