http://popups.lib.uliege.be/1373-5411/index.php?id=272 Index terms fr 0 http://popups.lib.uliege.be/1373-5411/index.php?id=4464 Present paper addresses an approach to determine optimal recruitment and transi tion strategies in strict hierarchical manpower system by the application of simula tion modeling and optimization methods. The transition model is represented in the form of discrete state space. The target values for each particular rank are deter mined by the user defined trajectory function. Optimal recruitment and transition dynamics is determined by the minimization of the differences between desired and actual state values. Analytical approach to the optimization is considered in order to provide proper control strategy. Fri, 11 Oct 2024 11:26:13 +0200 Fri, 11 Oct 2024 11:26:20 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=4464 http://popups.lib.uliege.be/1373-5411/index.php?id=845 This paper deals with a singular comportment of an incursive algorithm. This algorithm has been primary developed to optimise a production process. It is closed to classical genetic algorithms because it uses these major stages determination of n random solutions, evaluation of the solutions (in our case with the simulation of production process), selection of the best solution and reproduction according to the biologic rules of crossing over. Nevertheless the differences between this algorithm and a classical genetic algorithm are : the use of incursion in the selection's stage and the singularity of the reproduction stage. The algorithm enables indeed to optimise the system configuration by optimising the laws of reproduction. The "crossing over" becomes a specific case among huge other configurations. Despite we expect that the algorithm will be able to adapt his reproduction laws to the specificity of the system studied, the comportment of the optimisation, due to the use of incursion is unexpected and unfortunately unable to solve our production matter. Nevertheless this comportment is very interesting to study the consequences of the use of incursion with a genetic algorithm. Mon, 01 Jul 2024 14:01:30 +0200 Tue, 08 Oct 2024 17:16:15 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=845 http://popups.lib.uliege.be/1373-5411/index.php?id=3248 The paper is oriented to a non-standard method of optimizing various systems by means of object-oriented simulation. The substance of the method consists in modeling parallel development of several model variants so that they tend - within an evolutional environment - to the optimum. Each of the variants has its own simulated time and during that time it develops, communicates with the other variants and – being stimulated by them - it modifies its own parameters. The variants that develop in a parallel manner but in different time flows can be realistically interpreted in a "quasi-parallel" manner within a mono processor system ; that enables to reproduce the computing ; certain obstacles related to the quasi-parallelism can be surmounted. The programming technology, system metaphor and application are described. In the project management field the method renders it possible to estimate the real value of a project as an alternative of compound real option approach. Fri, 13 Sep 2024 13:19:35 +0200 Fri, 13 Sep 2024 13:19:45 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=3248 http://popups.lib.uliege.be/1373-5411/index.php?id=2739 We analyse the dynamics of simple class of neoclassical growth models with time-to-build. Time-to-build comes from the difference between the investment decisions and delivery of finished capital goods, as it was proposed by Tinbergen and Kalecki. This kind of delay in production of capital goods influence the optimal path of consumption of infinitely living economy. The optimal saving and consumption of households is chosen by the social planner in the way of solving the optimization problem with delay. Due to Kolmanovskii and Myshkis (1999) the classical Pontryagin maximum principle of dynamical optimization can be extended on the class of systems with time delay. The Hamiltonian for such systems can be simple constructed and the optimality condition can be derived. As a result we obtain a forward-looking Euler type equation. We compare the dynamics of economic systems with delay with the dynamics of their counterparts without the delay to show that both admit saddle type solutions. The paper points out the importance of the retarded-advanced dynamical systems in the economic theoretical investigations. Fri, 30 Aug 2024 15:05:42 +0200 Fri, 30 Aug 2024 15:05:51 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=2739 http://popups.lib.uliege.be/1373-5411/index.php?id=2195 Optimization theory is a key technology for inverse problems of reconstruction with applications in science, technology and economy. Discrete tomography is a modern research field which deals with finite objects from VLSI chip design or medical imaging. This paper focuses on the utilization of modern optimization methods to approximately resolve the NP-hard reconstruction problem of discrete tomography. Our new approaches and introductions are based on modeling and algorithms from coding theory and optimal experimental design. Here, we combine continuous and discrete optimization with exploiting geometrical symmetries, or more generally, equivariances, in a framework of statistical learning. Tue, 30 Jul 2024 13:22:50 +0200 Tue, 30 Jul 2024 13:23:02 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=2195 http://popups.lib.uliege.be/1373-5411/index.php?id=2051 In the present paper, for constructing the minimum risk estimators of state of stochastic systems, a new technique of invariant embedding of sample statistics in a loss function is proposed. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, an invariant embedding technique is independent of the choice of priors. It allows one to eliminate unknown parameters from the problem and to find the best invariant estimator, which has smaller risk than any of the well-known estimators. Also the problem of how to select the total number of the observations optimally when a constant cost is incurred for each observation taken is discussed. To illustrate the proposed technique, an example is given. Fri, 26 Jul 2024 16:07:39 +0200 Fri, 26 Jul 2024 16:07:49 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=2051 http://popups.lib.uliege.be/1373-5411/index.php?id=270 An image restoration is a typically ill-posed problem. Generally, regulalization scheme is used to avoid this problem. As a regularization operator, classical methods adopt one which may produce a too much smooth image. Parametric Projection Filter which has an ability to deal with colored observation noise is one of them. On the other hand, some methods based on a spatially adaptive regularization are proposed and successful in obtaining not so smooth one. However, it is assumed that observation noise is white, and the fidelity of images is not evaluated in the space of original images in these methods. In this paper, we propose a new restoration method by which we can evaluate the fidelity of images in the space of original images and obtain not so smooth one. We also verify the efficacy of the method by some numerical experiments. Wed, 19 Jun 2024 15:29:56 +0200 Wed, 19 Jun 2024 15:30:05 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=270