基于不确定控制理论的最优策略研究

本文在不确定理论的框架下,研究一类带背景状态变量的最优控制模型.在乐观值准则下,利用不确定动态规划的方法,证明了不确定最优性原则,得到最优性方程.作为应用,求解一个固定缴费(DC)型养老金的最优投资策略问题,在乐观值准则下,以工资变量为背景状态变量,建立养老金模型.通过求解不确定最优性方程得到最优投资策略和最优支付率.     

Uncertainty quantification for dynamics of geometrically nonlinear structures coupled with internal acoustic fluids in presence of sloshing and capillarity

In this paper, we propose an uncertainty quantification analysis, which is the continuation of a recent work performed in a deterministic framework. The fluid–structure system under consideration is the one experimentally studied in the sixties by Abramson, Kana, and Lindholm from the Southwest Research Institute under NASA contract. This coupled system is constituted of a linear acoustic liquid contained in an elastic tank that undergoes finite dynamical displacements, inducing geometrical nonlinear effects in the structure. The liquid has a free surface on which sloshing and capillarity effects are taken into account. The problem is expressed in terms of the acoustic pressure field in the fluid, of the displacement field of the elastic structure, and of the normal elevation field of the free surface. The nonlinear reduced-order model constructed in the recent work evoked above is reused for implementing the nonparametric probabilistic approach of uncertainties. The objective of this paper is to present a sensitivity analysis of this coupled fluid–structure system with respect to uncertainties and to use a classical statistical inverse problem for carrying out the experimental identification of the hyperparameter of the stochastic model. The analysis show a significant sensitivity of the displacement of the structure, of the acoustic pressure in the liquid, and of the free-surface elevation to uncertainties in both linear and geometrically nonlinear simulations.     

Analytic hierarchy process for multi-sensor data fusion based on belief function theory

Multi-sensor data fusion is an evolving technology whereby data from multiple sensor inputs are processed and combined. The data derived from multiple sensors can, however, be uncertain, imperfect, and conflicting. The present study is undertaken to help contribute to the continuous search for viable approaches to overcome the problems associated with data conflict and imperfection. Sensor readings, represented by belief functions, have to be fused according to their corresponding weights. Previous studies have often estimated the weights of sensor readings based on a single criterion. Mono-criteria approaches for the assessment of sensor reading weights are, however, often unreliable and inadequate for the reflection of reality. Accordingly, this work opts for the use of a multi-criteria decision aid. A modified Analytical Hierarchy Process (AHP) that incorporates several criteria is proposed to determine the weights of a sensor reading set. The approach relies on the automation of pairwise comparisons to eliminate subjectivity and reduce inconsistency. It assesses the weight of each sensor reading, and fuses the weighed readings obtained using a modified average combination rule. The efficiency of this approach is evaluated in a target recognition context. Several tests, sensitivity analysis, and comparisons with other approaches available in the literature are described.     

Measuring technical and environmental efficiency in a state-contingent technology

Most developed countries support farming activities through policies that are tailored to meet their specific social, economic and environmental objectives. Economic and environmental efficiency have recently become relevant targets of most of these policies, whose sound implementation can be enhanced by monitoring farm performance from a multidimensional perspective. This paper proposes farm-level technical and environmental efficiency measures that recognize the stochastic conditions in which production takes place. A state-contingent framework is used to model production uncertainty. An implementable representation of the technology is developed using data envelopment analysis. The application focuses on a sample of Catalan arable crop farms. Results suggest that technical efficiency is slightly lower in bad than in good growing conditions. Nitrogen pollution can decrease substantially more under good than bad growing conditions.     

A new distance measure including the weak preference relation: Application to the multiple criteria aggregation procedure for mixed evaluations

We introduce a new distance measure between two preorders that captures indifference, strict preference, weak preference and incomparability relations. This measure is the first to capture weak preference relations. We illustrate how this distance measure affords decision makers greater modeling power to capture their preferences, or uncertainty and ambiguity around them, by using our proposed distance measure in a multiple criteria aggregation procedure for mixed evaluations.     

Interval,ellipsoidal, and super-ellipsoidal calculi for experimental and theoretical treatment of uncertainty: Which one ought to be preferred?

In this study we compare three calculi listed in the title for analysis of structures involving uncertainty. The main idea is based on the consideration that the maximum structural response predicted by the preferred theory ought to be minimal, and the minimum structural response predicted by the preferred theory ought to be maximal, to constitute a lower overestimation. We present analytic results that allow one to calculate the structural response via the interval, ellipsoidal or super-ellipsoidal calculus. We provide several examples of truss structures and illustrate that in different situations, depending on the available data, one of these calculi ought to be preferred. Conclusion is made on the preferable approach to be the super-ellipsoidal calculus.     

Determination of methylmercury in marine sediment samples: Method validation and occurrence data

The determination of methylmercury (MeHg) in sediment samples is a difficult task due to the extremely low MeHg/THg (total mercury) ratio and species interconversion. Here, we present the method validation of a cost-effective fit-for-purpose analytical procedure for the measurement of MeHg in sediments, which is based on aqueous phase ethylation, followed by purge and trap and hyphenated gas chromatography–pyrolysis–atomic fluorescence spectrometry (GC–Py–AFS) separation and detection. Four different extraction techniques, namely acid and alkaline leaching followed by solvent extraction and evaporation, microwave-assisted extraction with 2-mercaptoethanol, and acid leaching, solvent extraction and back extraction into sodium thiosulfate, were examined regarding their potential to selectively extract MeHg from estuarine sediment IAEA-405 certified reference material (CRM). The procedure based on acid leaching with HNO₃/CuSO₄, solvent extraction and back extraction into Na₂S₂O₃ yielded the highest extraction recovery, i.e., 94 ± 3% and offered the possibility to perform the extraction of a large number of samples in a short time, by eliminating the evaporation step. The artifact formation of MeHg was evaluated by high performance liquid chromatography coupled to inductively coupled plasma mass spectrometry (HPLC–ICP–MS), using isotopically enriched Me²⁰¹Hg and ²⁰²Hg and it was found to be nonexistent. A full validation approach in line with ISO 17025 and Eurachem guidelines was followed. With this in mind, blanks, selectivity, working range (1–800 pg), linearity (0.9995), recovery (94–96%), repeatability (3%), intermediate precision (4%), limit of detection (0.45 pg) and limit of quantification (0.85 pg) were systematically assessed with CRM IAEA-405. The uncertainty budget was calculated and the major contribution to the combined uncertainty (16.24%, k = 2) was found to arise from the uncertainty associated with recovery (74.1%). Demonstration of traceability of measurement results is also presented. The validated measurement procedure was applied to the determination of MeHg incurred in sediments from a highly polluted and scarcely studied area in the Caribbean region.     

Convergence properties and practical estimation of the probability of rank reversal in pairwise comparisons for multi-criteria decision making problems

In this paper, we address the impact of uncertainty introduced when the experts complete pairwise comparison matrices, in the context of multi-criteria decision making. We first discuss how uncertainty can be quantified and modeled and then show how the probability of rank reversal scales with the number of experts. We consider the impact of various aspects which may affect the estimation of probability of rank reversal in the context of pairwise comparisons, such as the uncertainty level, alternative preference scales and different weight estimation methods. We also consider the case where the comparisons are carried out in a fuzzy manner. It is shown that in most circumstances, augmenting the size of the expert group beyond 15 produces a small change in the probability of rank reversal. We next address the issue of how this probability can be estimated in practice, from information gathered simply from the comparison matrices of a single expert group. We propose and validate a scheme which yields an estimate for the probability of rank reversal and test the applicability of this scheme under various conditions. The framework discussed in the paper can allow decision makers to correctly choose the number of experts participating in a pairwise comparison and obtain an estimate of the credibility of the outcome.     

Uncertain multiobjective traveling salesman problem

Traveling salesman problem is a fundamental combinatorial optimization model studied in the operations research community for nearly half a century, yet there is surprisingly little literature that addresses uncertainty and multiple objectives in it. A novel TSP variation, called uncertain multiobjective TSP (UMTSP) with uncertain variables on the arc, is proposed in this paper on the basis of uncertainty theory, and a new solution approach named uncertain approach is applied to obtain Pareto efficient route in UMTSP. Considering the uncertain and combinatorial nature of UMTSP, a new ABC algorithm inserted with reverse operator, crossover operator and mutation operator is designed to this problem, which outperforms other algorithms through the performance comparison on three benchmark TSPs. Finally, a new benchmark UMTSP case study is presented to illustrate the construction and solution of UMTSP, which shows that the optimal route in deterministic TSP can be a poor route in UMTSP.