Search results for "Mathematical optimization"
showing 10 items of 1300 documents
An LMI Approach to Exponential Stock Level Estimation for Large-Scale Logistics Networks
2013
This article aims to present a convex optimization approach for exponential stock level estimation problem of large-scale logistics networks. The model under consideration presents the dependency and interconnections between the dynamics of each single location. Using a Lyapunov function, new sufficient conditions for exponential estimation of the networks are driven in terms of linear matrix inequalities (LMIs). The explicit expression of the observer gain is parameterized based on the solvability conditions. A numerical example is included to illustrate the applicability of the proposed design method.
Stability analysis and controller design for a class of T-S fuzzy Markov jump system with uncertain expectation of packet dropouts
2013
This paper is concerned with an H∞ control for a class of Takagi-Sugeno (T-S) fuzzy Markov jump system under unreliable communication links. It is assumed that the transition probabilities determining the dynamical behavior of the underlying system are partially unknown and the communication links between the plant and the controller are imperfect (the packet dropouts occur intermittently). In this paper, a more practical scenario is considered in the setting, i.e., the expectation of packet losses represented as a description of Bernoulli-distributed stochastic process is uncertain. Attention is focused on the design of H∞ controllers such that the closed-loop system is stochastically stab…
Dynamic Output-Feedback Passivity Control for Fuzzy Systems under Variable Sampling
2013
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/767093 Open Access This paper concerns the problem of dynamic output-feedback control for a class of nonlinear systems with nonuniform uncertain sampling via Takagi-Sugeno (T-S) fuzzy control approach. The sampling is not required to be periodic, and the state variables are not required to be measurable. A new type fuzzy dynamic output-feedback sampled-data controller is constructed, and a novel time-dependent Lyapunov-Krasovskii functional is chosen for fuzzy systems under variable sampling. By using Lyapunov stability theory, a sufficie…
Optimization of anemia treatment in hemodialysis patients via reinforcement learning
2013
Objective: Anemia is a frequent comorbidity in hemodialysis patients that can be successfully treated by administering erythropoiesis-stimulating agents (ESAs). ESAs dosing is currently based on clinical protocols that often do not account for the high inter- and intra-individual variability in the patient's response. As a result, the hemoglobin level of some patients oscillates around the target range, which is associated with multiple risks and side-effects. This work proposes a methodology based on reinforcement learning (RL) to optimize ESA therapy. Methods: RL is a data-driven approach for solving sequential decision-making problems that are formulated as Markov decision processes (MDP…
A flexible approach to the crossing hazards problem
2010
We propose a simple and flexible framework for the crossing hazards problem. The method is not confined to two-sample problems, but may also work with continuous exposure variables whose effect changes its sign at some time-point of the observed follow-up time. Penalized partial likelihood estimation relies upon the assumption of a smooth hazard ratio via low-rank basis splines with a conventional difference penalty to ensure smoothness, and additional ad hoc penalties to obtain restricted estimates useful in the context of crossing hazards. The framework naturally also leads to a statistical test that has good power for revealing a global effect under several alternatives, including crossi…
Tool replacement with adaptive control in a non-stationary non-periodic stochastic process
1991
Abstract The problem of optimum tool replacement is studied in the case in which tool performance is characterized by progressive decay over time following stochastic laws. A control system is assumed which detects, continuously or at fixed intervals, the service state of the tool. Assuming that the service state of the tool affects the marginal cost of production, the latter is used in order to minimize the unit production cost for an unlimited production horizon. The replacement policy proposed is able to update itself in process by means of an iterative procedure which converges to a conditioned optimum. The effectiveness of such a policy is demonstrated analytically, and illustrative ex…
A contribution to the linear programming approach to joint cost allocation: Methodology and application
2009
Abstract The linear programming (LP) approach has been commonly proposed for joint cost allocation purposes. Within a LP framework, the allocation rules are based on a marginal analysis. Unfortunately, the additivity property which is required to completely allocate joint costs fails in presence of capacity, institutional or environmental constraints. In this paper, we first illustrate that the non allocated part can be interpreted as a type of producer’s surplus. Then, by using the information contained in the Simplex tableau we propose an original two-stage methodology based on the marginal costs and the production elasticity of input factors to achieve an additive cost allocation pattern…
Beyond Viner: Smoothed Cost Curves and Co-Detetermination of Output and Production Capacity
2017
We address two problems of traditional cost functions: the discontinuity caused by the production capacity (the marginal cost abruptly becomes infinite when production capacity is reached) and the production capacity is artificially exogenous. So, we introduce a smoothed form of marginal cost function. It progressively tends to infinity when it approaches to the production capacity. Then, we prove that it is perfectly possible to determine directly output, fixed costs and production capacity simultaneously, even if this could lead to a system of equations that is not so elementary to solve because it includes a Lambert function. We also show that the smoothed cost function prevails in both …
Minimising value-at-risk in a portfolio optimisation problem using a multi-objective genetic algorithm
2011
[EN] In this paper, we develop a general framework for market risk optimisation that focuses on VaR. The reason for this choice is the complexity and problems associated with risk return optimisation (non-convex and non-differential objective function). Our purpose is to obtain VaR efficient frontiers using a multi-objective genetic algorithm (GA) and to show the potential utility of the algorithm to obtain efficient portfolios when the risk measure does not allow calculating an optimal solution. Furthermore, we measure differences between VaR efficient frontiers and variance efficient frontiers in VaR-return space and we evaluate out-sample capacity of portfolios on both bullish and bearis…
Comparative evaluation of some interactive reference point-based methods for multi-objective optimisation
1999
Many real-world optimisation applications include several conflicting objectives of possibly nondifferentiable character. However, the lack of computationally efficient, interactive methods for nondifferentiable multi-objective optimisation problems is apparent. To satisfy this demand, a method called NIMBUS has been developed. Two versions of the basic method are presented and compared both theoretically and computationally. In order to give variety to the comparison, a related approach, called reference direction method is included. Theoretically, the methods differ in handling the information requested from the user. Numerical experiments indicate differences in computational efficiency …