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Kinetic systems form a wide nonlinear system class with good descriptive power that can efficiently be used for the dynamical modeling of non-negative models emerging not only in (bio)chemistry but in other important scientific and engineering fields as well. The directed graph structure assigned to kinetic models give us important information about the qualitative dynamical properties of the system...
In the process of achieving enterprise value maximization, agricultural enterprises will face external and internal risks of uncertainty. The premise of risk control is to conduct a risk assessment. The key of risk assessment is to establish and optimize the evaluation index system. In this paper, we use factor analysis to optimize the evaluation index system of agricultural enterprises risk. The...
Irreversible investments with largest outlay made with incomplete information are the mainstay of the oilfield development. Real Options Analysis (ROA) is a useful tool for making investment decisions under market uncertainty. Normal information generates continuous mean-reverting process for oil prices, whereas random abnormal information generates discrete jumps of random size. We evaluate an oilfield...
Lose aversion refers to the psychological phenomenal that losses and disadvantages have greater impact on preferences than gains and advantages. While to a considerable extent, risk aversion as it is commonly observed is caused by loss aversion. This paper integrates Markowitz's efficient frontier theory into lose aversion function, and the portfolio decision of lose averse investors has been discussed...
This study develops a robust modeling and stabilization framework for an interconnected lake-aquifer system in the field of hydrology. The conventional lake-aquifer dynamics are transformed into a multi-input multioutput linear time-invariant model with a bounded uncertainty. The robust performance of the system is obtained through an H-infinity controller to address a bounded model uncertainty, satisfactory...
Optimization method with triangular fuzzy numbers is introduced to describe the expected yield rate and risk loss of securities investment, and a combinational fuzzy optimization model of inclinations with exchange fee to avoid risks is presented in this paper. The experimental results on the data investigated from real-world securities markets show that our new method exploits a new strategy for...
The e-commerce markets make it easier for buyers to purchase products from distant seller, but the lack of the conventional ways to assess the quality of a product may brings on the cyber 'lemons' problem. This paper builds the equilibrium model between e-commerce and traditional marketplaces. This paper concludes that if 'lemons' problem persists in both two marketplaces, a sub-optimal equilibrium...
In order to explore relation between evaluation results from different methods, a new model is proposed to choose the optimal scheme based on set pair analysis though comparing the affiliation degree among the given schemes in this paper. Considering the discrepancy degree of evaluation results, it comes up with a method for selecting optimum from evaluation schemes, using the quantity of ranking...
In this study, a two-level scheme with robust dynamic real-time optimization and distributed model predictive control (DMPC) is presented for plant-wide processes. On the top layer, chance-constrained programming (CCP) is employed in the real-time optimization with economic and model uncertainties, in which the constraints containing stochastic parameters are guaranteed to be satisfied at a high level...
Recent years have witnessed an obvious increase in cooperation between the public and private sectors for the development and operation of infrastructure for a wide range of economic activities. Public-private partnership (PPP) provides an alternative way of involving the private sector in the delivery of public services. PPP is not only a financing pattern in the area of government investment, but...
Traditional security models and single security technology cannot keep up with the change of complicated network structure and varied intrusion measure. Network security manage based on optimization has traits of low manage cost, high agility, wide applicability. This paper introduces network security management based on non-optimum system theory into new network security model, and emphases on its...
The operation process for a class of closed-loop logistic system with uncertain demands is considered. This system contains multiple suppliers, manufactories, distribution centers and customers, and the demands of customers are uncertainty. Based on the early research results, the integration of forward and reverse logistics was investigated. By using the robust optimization method based on scenario...
Research regarding supply chain optimization has been performed for a long time. However, it's only in the last decade that the research community has started to investigate multi-objective optimization for supply chains. Supply chains are in general complex networks composed of autonomous entities whereby multiple performance measures in different levels, which in most cases are in conflict with...
For the oil-depot undertakes specific tasks with the timeliness and economy requirements, the oil-depot geographical configuration optimum is discussed and the evaluation indicators system of the configuration area has been put forward. Meanwhile, the oil-depot geographical configuration model has been established by using uncertain linguistic information and multi-attribute group decision-making...
This paper considers the optimization problem of biochemical systems represented by the S-system formalism under uncertainty. The uncertain optimization problem is firstly proposed and is then transformed into an equivalent problem that can be solved with a modified iterative IOM algorithm. Finally, the example of tryptophan biosynthesis is performed to proposed framework of optimization under kinetic...
Summary form only given. There is an extensive literature on decision-making under uncertainty. Unfortunately, up to day there are no valid decision principles. The widely used principle of maximization of expected utility has serious shortcomings. The first approach in classical theory of choice was formulated axiomatically in the expected utility theory of von Neumann and Morgenstern and is the...
This paper addresses the portfolio selection problem in a robust manner. In practice, it is difficult to collect all information to determine the precise bounds of the box uncertainty set used in robust portfolio optimization. To solve this problem, we introduce a novel uncertainty set: interval random uncertainty. We apply our interval random chance-constrained programming to robust semi-absolute...
We consider a call center staffing problem with two types of customers of which the arrival rates are allowed to be a random and non-stationary. In order to efficiently cope with such random workload fluctuations, the workforce presents some flexibility: the agents can be, in real-time, affected to each type of customers according to the instantaneously observed workload and the associated/relative...
Assuming that individuals are altruistic, this paper employs an overlapping generations model with lifetime uncertainty to study the partially funded public pension in China. By comparing the market economy equilibrium with the social optimum allocation, we find the optimal firm contribution rate. Our simulation results show that this rate increases when the life expectancy rises, while decreases...
As a result of deregulated markets, the utilities are exposed to different generation planning uncertainties such as energy exchange and gas prises. The generation planning time horizon covers a period of one month to one year. Deterministic techniques are no longer suitable and further more increased the planning risks. To solve this complicated problem the whole system is decomposed into subsystems...
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