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21.
Background risk can influence the performance of insurance markets that must deal with adverse selection when applicants are risk vulnerable, since they are more averse to bearing the insurable risk as a result of their exposures to background risk. We show that background risk always results in a lower deductible for the incentive constrained contract, and that a broader range of markets attains the stable sequential equilibrium cross-subsidized pair of separating contracts. We conclude that background risk always improves the performance of markets for coverage against (insurable) foreground risks that must deal with adverse selection. We also find, however, that these improvements are never sufficient to offset the cost to insureds of bearing the background risk. 相似文献
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Informational Entropy: a Failure Tolerance and Reliability Surrogate for Water Distribution Networks
Tiku T. Tanyimboh 《Water Resources Management》2017,31(10):3189-3204
Evolutionary algorithms are used widely in optimization studies on water distribution networks. The optimization algorithms use simulation models that analyse the networks under various operating conditions. The solution process typically involves cost minimization along with reliability constraints that ensure reasonably satisfactory performance under abnormal operating conditions also. Flow entropy has been employed previously as a surrogate reliability measure. While a body of work exists for a single operating condition under steady state conditions, the effectiveness of flow entropy for systems with multiple operating conditions has received very little attention. This paper describes a multi-objective genetic algorithm that maximizes the flow entropy under multiple operating conditions for any given network. The new methodology proposed is consistent with the maximum entropy formalism that requires active consideration of all the relevant information. Furthermore, an alternative but equivalent flow entropy model that emphasizes the relative uniformity of the nodal demands is described. The flow entropy of water distribution networks under multiple operating conditions is discussed with reference to the joint entropy of multiple probability spaces, which provides the theoretical foundation for the optimization methodology proposed. Besides the rationale, results are included that show that the most robust or failure-tolerant solutions are achieved by maximizing the sum of the entropies. 相似文献
27.
Expressions for marginal distribution functions of sequential order statistics and generalized order statistics are presented without any restrictions imposed on the model parameters. The results are related to the relevation transform, to the distribution of the product of Beta distributed random variables, and to Meijers G-functions. Some selected applications in the areas of moments, conditional distributions, recurrence relations, and reliability properties are shown.
Key words:Order statistics; Generalized order statistics; Sequential order statistics; Record values; Distribution theory; Meijers G-function; Recurrence relations; Reliability properties. 相似文献
28.
Kim C. Border 《Economic Theory》2007,31(1):167-181
This note uses the Theorem of the Alternative to prove new results on the implementability of general, asymmetric auctions,
and to provide simpler proofs of known results for symmetric auctions. The tradeoff is that type spaces are taken to be finite. 相似文献
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Design of Barrages with Genetic Algorithm Based Embedded Simulation Optimization Approach 总被引:2,自引:2,他引:0
Raj Mohan Singh 《Water Resources Management》2011,25(2):409-429
Barrages are hydraulic structures constructed across rivers to divert flow into irrigation canals or power generation channels.
The most of these structures are founded on permeable foundation. The optimum cost of these structures is nonlinear function
of factors that cause the seepage forces under the structure. There is, however, no procedure to ascertain the basic barrage
parameters such as depth of sheet piles or cutoffs and the length and thickness of floor in a cost–effective manner. In this
paper, a nonlinear optimization formulation (NLOF), which consists of an objective function of minimizing total cost, is solved
using genetic algorithm (GA). The mathematical model that represents the subsurface flow is embedded in the NLOF. The applicability
of the approach has been illustrated with a typical example of barrage profile. The results obtained in this study shows drastic
cost savings when the proposed NLOF is solved using GA than that of using classical optimization technique and conventional
method. A parametric analysis has also been performed to study the effect of varying soil and hydrological conditions on design
parameters and on over all cost. 相似文献