scholarly journals Optimal Design Strategies for Sibling Studies with Binary Exposures

2014 ◽  
Vol 10 (2) ◽  
Author(s):  
Zhigang Li ◽  
Ian W. McKeague ◽  
Lambert H. Lumey
Keyword(s):  
Optimal Strategy ◽  
Optimal Strategies ◽  
Binary Outcomes ◽  
Binary Response ◽  
Efficient Design ◽  
Design Strategies ◽  
Sibling Pairs ◽  
Family Level ◽  
Continuous Outcomes ◽  
Study Power

AbstractSibling studies have become increasingly popular because they provide better control over confounding by unmeasured family-level risk factors than can be obtained in standard cohort studies. However, little attention has been devoted to the development of efficient design strategies for sibling studies in terms of optimizing power. We here address this issue in commonly encountered types of sibling studies, allowing for continuous and binary outcomes and varying numbers of exposed and unexposed siblings. For continuous outcomes, we show that in families with sibling pairs, optimal study power is obtained by recruiting discordant (exposed–control) pairs of siblings. More generally, balancing the exposure status within each family as evenly as possible is shown to be optimal. For binary outcomes, we elucidate how the optimal strategy depends on the variation of the binary response; as the within-family correlation increases, the optimal strategy tends toward only recruiting discordant sibling pairs (as in the case of continuous outcomes). R code for obtaining the optimal strategies is included.

scholarly journals Optimal, near-optimal, and robust epidemic control

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Dylan H. Morris ◽  
Fernando W. Rossine ◽  
Joshua B. Plotkin ◽  
Simon A. Levin
Keyword(s):  
Robust Control ◽  
Disease Control ◽  
Epidemic Model ◽  
Optimal Strategy ◽  
Policy Design ◽  
Optimal Strategies ◽  
Economic Costs ◽  
Short Period ◽  
Intervention Policy ◽  
Pharmaceutical Interventions

AbstractIn the absence of drugs and vaccines, policymakers use non-pharmaceutical interventions such as social distancing to decrease rates of disease-causing contact, with the aim of reducing or delaying the epidemic peak. These measures carry social and economic costs, so societies may be unable to maintain them for more than a short period of time. Intervention policy design often relies on numerical simulations of epidemic models, but comparing policies and assessing their robustness demands clear principles that apply across strategies. Here we derive the theoretically optimal strategy for using a time-limited intervention to reduce the peak prevalence of a novel disease in the classic Susceptible-Infectious-Recovered epidemic model. We show that broad classes of easier-to-implement strategies can perform nearly as well as the theoretically optimal strategy. But neither the optimal strategy nor any of these near-optimal strategies is robust to implementation error: small errors in timing the intervention produce large increases in peak prevalence. Our results reveal fundamental principles of non-pharmaceutical disease control and expose their potential fragility. For robust control, an intervention must be strong, early, and ideally sustained.

scholarly journals Improving the criteria for choosing the strategies in management by geotechnical systems

2019 ◽  
Vol 109 ◽  
pp. 00048
Author(s):  
Yevhen Lapshyn ◽  
Robert Molchanov ◽  
Borys Blyuss ◽  
Nataliia Osadcha
Keyword(s):  
Game Theory ◽  
Optimal Strategy ◽  
Optimal Strategies ◽  
Mineral Deposits ◽  
Underground Space ◽  
Infrastructure Development ◽  
Main Indicator ◽  
Geological Conditions ◽  
Geological Faults

The conclusion has been made about the necessity to choose the optimal strategies for management by geotechnical systems, based on the analysis of geological faults, which are the main indicator of the mining and geological conditions that characterize the mineral deposits, as well as on the parameters for the infrastructure development of the underground space. The methodological peculiarity of solving the problems set is the use of game theory with modified criteria of Wald, maximax and Savage, since the manifestation of specific geological faults is probabilistic in nature. When choosing the optimal strategy, the average linear deviations of gains or risks are taken into account.

Co-Evolutionary Algorithm between Helicopter and Submarine

2015 ◽  
Vol 719-720 ◽  
pp. 1229-1235
Author(s):  
Ying Chun Chen ◽  
Xian Hua Wang
Keyword(s):  
Evolutionary Algorithm ◽  
Optimal Strategy ◽  
Theoretical Foundation ◽  
Optimal Strategies ◽  
Evaluation Methods ◽  
Movement Model ◽  
Fitness Evaluation ◽  
Detection Model ◽  
Ocean Environment

A co-evolutionary algorithm is proposed for the play between a submarine and a helicopter equipped with dipping sonar. First, the theoretical foundation of co-evolution is elaborated. The movement model of helicopter and submarine, the detection model of dipping sonar under certain ocean environment are established. After defining the strategies of helicopter and submarine and fitness evaluation methods, the process of co-evolutionary algorithm is described. The optimal strategy of helicopter after helicopter evolution, and the optimal strategies of both helicopter and submarine after co-evolution are given

The structure of nearly-optimal quantum strategies for the non-local XOR games

2016 ◽  
Vol 16 (13&14) ◽  
pp. 1191-1211 ◽  
Author(s):  
Dimeter Ostrev
Keyword(s):  
Algebraic Structure ◽  
Optimal Strategy ◽  
Infinite Family ◽  
Optimal Strategies ◽  
Non Local ◽  
Quantum Strategies

We consider the infinite family of non-local games CHSH(n). We consider nearly-optimal strategies for CHSH(n). We introduce a notion of approximate homomorphism for strategies and show that any nearly-optimal strategy for CHSH(n) is approximately homomorphic to the canonical optimal CHSH(n) strategy. This demonstrates that any nearly-optimal CHSH(n) strategy must approximately contain the algebraic structure of the canonical optimal strategy.

Optimal Strategies for Deteriorating Inventory Systems Under Trapezoidal Type Demand

2018 ◽  
pp. 1-31
Author(s):  
Kunal Tarunkumar Shukla ◽  
Mihir S. Suthar
Keyword(s):  
Sensitivity Analysis ◽  
Continuous Function ◽  
Optimal Strategy ◽  
Piecewise Linear ◽  
Optimal Strategies ◽  
Literature Survey ◽  
Inventory Systems ◽  
Future Research ◽  
Partial Backlogging ◽  
Demand Rate

In this chapter, we study different inventory systems with trapezoidal demand rate, i.e., demand rate is a piecewise linear and continuous function. This chapter presents mathematical formulations of optimal replenishment policies for items with trapezoidal demand rate. Section 1 presents detailed literature survey for inventory systems with ramp type and trapezoidal type demand. In Section 2, Formulation technique for inventory system of items, which follows trapezoidal type demand rate. Section 3 presents effect of deterioration in model discussed in Section 2. Optimal strategy for deteriorating items with expiration dates under trapezoidal type demand and partial backlogging is discussed in Section 4. In Section 5, sensitivity analysis is carried out and chapter is concluded along with future research scope in Section 6.

Optimal strategies for discovering new species in continuous time

1989 ◽  
Vol 26 (04) ◽  
pp. 695-706
Author(s):  
Gerold Alsmeyer ◽  
Albrecht Irle
Keyword(s):  
New Species ◽  
Optimal Stopping ◽  
Continuous Time ◽  
Optimal Strategy ◽  
Stopping Time ◽  
Optimal Strategies ◽  
Distinct Species ◽  
Natural Generalization ◽  
General Point ◽  
Time Optimal

Consider a population of distinct species Sj , j∈J, members of which are selected at different time points T 1 , T 2,· ··, one at each time. Assume linear costs per unit of time and that a reward is earned at each discovery epoch of a new species. We treat the problem of finding a selection rule which maximizes the expected payoff. As the times between successive selections are supposed to be continuous random variables, we are dealing with a continuous-time optimal stopping problem which is the natural generalization of the one Rasmussen and Starr (1979) have investigated; namely, the corresponding problem with fixed times between successive selections. However, in contrast to their discrete-time setting the derivation of an optimal strategy appears to be much harder in our model as generally we are no longer in the monotone case. This note gives a general point process formulation for this problem, leading in particular to an equivalent stopping problem via stochastic intensities which is easier to handle. Then we present a formal derivation of the optimal stopping time under the stronger assumption of i.i.d. (X 1 , A 1) (X2, A2 ), · ·· where Xn gives the label (j for Sj ) of the species selected at Tn and An denotes the time between the nth and (n – 1)th selection, i.e. An = Tn – Tn– 1. In the case where even Xn and An are independent and An has an IFR (increasing failure rate) distribution, an explicit solution for the optimal strategy is derived as a simple consequence.

scholarly journals The Noisy Secretary Problem and Some Results on Extreme Concomitant Variables

2012 ◽  
Vol 49 (3) ◽  
pp. 821-837 ◽  
Author(s):  
Abba M. Krieger ◽  
Ester Samuel-Cahn
Keyword(s):  
Optimal Strategy ◽  
Noisy Data ◽  
Optimal Strategies ◽  
Secretary Problem ◽  
Distribution Free ◽  
Concomitant Variables ◽  
Noisy Observation ◽  
Independent And Identically Distributed

The classical secretary problem for selecting the best item is studied when the actual values of the items are observed with noise. One of the main appeals of the secretary problem is that the optimal strategy is able to find the best observation with a nontrivial probability of about 0.37, even when the number of observations is arbitrarily large. The results are strikingly different when the qualities of the secretaries are observed with noise. If there is no noise then the only information that is needed is whether an observation is the best among those already observed. Since the observations are assumed to be independent and identically distributed, the solution to this problem is distribution free. In the case of noisy data, the results are no longer distribution free. Furthermore, we need to know the rank of the noisy observation among those already observed. Finally, the probability of finding the best secretary often goes to 0 as the number of observations, n, goes to ∞. The results heavily depend on the behavior of pn, the probability that the observation that is best among the noisy observations is also best among the noiseless observations. Results involving optimal strategies if all that is available is noisy data are described and examples are given to elucidate the results.

Evolution of Hunter–Gatherer Strategies with a Genetically Inspired Algorithm

1998 ◽  
Vol 09 (04) ◽  
pp. 547-554 ◽  
Author(s):  
Pat Sutton ◽  
A. Georgallas ◽  
D. L. Hunter ◽  
N. Jan ◽  
R. J. Nash ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Optimal Strategy ◽  
Point Mutations ◽  
Optimal Strategies ◽  
Resource Exploitation

We address the following: Are there several optimal strategies for a hunter-gatherer society in a given environment, in which the society has an evolving level of technology and/or skills? We use the Genetic Algorithm, with point mutations, to facilitate the search for these strategies. We find that, in a generous environment, several optimal strategies are possible; there is no unique optimal strategy. We are now in a position, with the Genetic Algorithm, to assess different approaches to resource exploitation and the role of contingency.

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