Integrated game-theory modelling for multi enterprise-wide coordination and collaboration under uncertain competitive environment

In this work, an integrated Game Theory (GT) approach is developed for the coordination of multi-enterprise Supply Chains (SCs) in a competitive uncertain environment. The conflicting goals of the different participants are solved through coordination contracts using a non-cooperative non-zero-sum Stackelberg game under the leadership of the manufacturer. The Stackelberg payoff matrix is built under the nominal conditions, and then evaluated under different probable uncertain scenarios using a Monte-Carlo simulation. The competition between the Stackelberg game players and the third parties is solved through a Nash Equilibrium game. A novel way to analyze the game outcome is proposed based on a win–win Stackelberg set of “Pareto-frontiers”. The benefits of the resulting MINLP tactical models are illustrated by a case study with different vendors around a client SC. The results show that the coordinated decisions lead to higher expected payoffs compared to the standalone case, while also leading to uncertainty reduction.Peer ReviewedPostprint (author's final draft

Implemented Crime Prevention Strategies of PNP in Salug Valley, Zamboanga Del Sur, Philippines

Abstract – This study aimed primarily to determine the effectiveness of crime prevention strategies implemented by the Salug Valley Philippine National Police (PNP) in terms of Police Integrated Patrol System, Barangay Peacekeeping Operation, Anti-Criminality Operation, Integrated Area Community Public Safety services, Bantay Turista and School Safety Project as evaluated by 120 inhabitants and 138 PNP officers from four Municipalities of Salug Valley Zamboanga del Sur. Stratified random sampling was utilized in determining the respondents. Index crime rate were correlated with the crime prevention strategies of the PNP in town of Salug Valley. A descriptive method of research was applied in this study utilizing self-made questionnaire. The data collected were analyzed using the main statistical tools like frequency count, percentage, mean computation, Kruskal Wallis Analysis of Variance and simple correlation. Findings of the study revealed that the crime prevention strategies in four (4) municipalities were “much effective” to include Integrated Patrol System, Barangay Peace Keeping Operations, Anti-Criminality Operations, Integrated Area Community Public Safety Services, Bantay Turista and School Safety Project in connection to the responses of 158 participants. There is a significant relationship between crime prevention strategies employed and index crime rate

Bayesian optimisation for likelihood-free cosmological inference

Many cosmological models have only a finite number of parameters of interest, but a very expensive data-generating process and an intractable likelihood function. We address the problem of performing likelihood-free Bayesian inference from such black-box simulation-based models, under the constraint of a very limited simulation budget (typically a few thousand). To do so, we adopt an approach based on the likelihood of an alternative parametric model. Conventional approaches to approximate Bayesian computation such as likelihood-free rejection sampling are impractical for the considered problem, due to the lack of knowledge about how the parameters affect the discrepancy between observed and simulated data. As a response, we make use of a strategy previously developed in the machine learning literature (Bayesian optimisation for likelihood-free inference, BOLFI), which combines Gaussian process regression of the discrepancy to build a surrogate surface with Bayesian optimisation to actively acquire training data. We extend the method by deriving an acquisition function tailored for the purpose of minimising the expected uncertainty in the approximate posterior density, in the parametric approach. The resulting algorithm is applied to the problems of summarising Gaussian signals and inferring cosmological parameters from the Joint Lightcurve Analysis supernovae data. We show that the number of required simulations is reduced by several orders of magnitude, and that the proposed acquisition function produces more accurate posterior approximations, as compared to common strategies.Comment: 16+9 pages, 12 figures. Matches PRD published version after minor modification

Tariff Reforms with Rigid Wages

This paper analyses the effects of tariff reforms on welfare and market access in a competitive small open economy that is characterised by involuntary unemployment due to non-market clearing wages that are fixed either in terms of the numeraire or in real terms. We show that recent tariff-reform results can be extended to integrated reforms of tariffs and the wage rate, and that the inherent tension between reforms that increase welfare and market access carry over. We also derive welfare increasing tariff-reform strategies that keep the wage rate constant, and show that this tension may be attenuated.Tariff Reform, Unemployment, Small Open Economy

Stochastic Representations of Ion Channel Kinetics and Exact Stochastic Simulation of Neuronal Dynamics

In this paper we provide two representations for stochastic ion channel kinetics, and compare the performance of exact simulation with a commonly used numerical approximation strategy. The first representation we present is a random time change representation, popularized by Thomas Kurtz, with the second being analogous to a "Gillespie" representation. Exact stochastic algorithms are provided for the different representations, which are preferable to either (a) fixed time step or (b) piecewise constant propensity algorithms, which still appear in the literature. As examples, we provide versions of the exact algorithms for the Morris-Lecar conductance based model, and detail the error induced, both in a weak and a strong sense, by the use of approximate algorithms on this model. We include ready-to-use implementations of the random time change algorithm in both XPP and Matlab. Finally, through the consideration of parametric sensitivity analysis, we show how the representations presented here are useful in the development of further computational methods. The general representations and simulation strategies provided here are known in other parts of the sciences, but less so in the present setting.Comment: 39 pages, 6 figures, appendix with XPP and Matlab cod