We propose a gradient-based method to solve quasiconvex optimization problems through decomposed optimization and prove local superlinear convergence under mild regularity assumptions at the optimal solution. A practical implementation further provides global convergence while maintaining the...

Background When pairwise comparisons are used to express preferences for alternatives or judgments on criteria's importance, several methods can be used to derive priorities in multi-criteria decision-making. In the case of inconsistency, different methods give different results. Objectives The...

Globally optimal free flight trajectory optimization can be achieved with a combination of discrete and continuous optimization. A key requirement is that Newton's method for continuous optimization converges in a sufficiently large neighborhood around a minimizer. We show in this paper that,...

We propose a data-based approximation of the effects of trade sanctions. We validate the approximation by comparing it with exact responses simulated from a canonical multi-country multi-sector model. The approximation is palatable for a broad range of elasticities of substitution, except for...

1 Descartes’ Analytic Geometry -- 1.1 Lines -- 1.2 Quadratic Equations -- 1.3 Lines and Circles -- 1.4 Hyperbole -- 1.5 Parabola -- 1.6 Long Division of Polynomials and Horner’s Rule -- 1.7 Roots of Polynomials -- 1.8 Tangents to Polynomial Curves -- 1.9 Derivatives of Polynomials -- 1.10...

IoT Based Smartbin for Smart Campus -- Aspect of Artificial Intelligence in Dealing with Mental Health Disorders in Adolescents -- Mathematical Modeling and Analysis of Spread of Crime in a Society -- Approximate Solution of Kawahara KdV and modified Kawahara KdV Equation by using RDTM -- Dental...

The exact distribution of a quadratic form in n standard normal variables, Q; say, (or, equivalently, a linear combination of independent chi-squared variates) is, except in special cases, quite complicated. This has led to many proposals for approximating the distribution by a more tractable...

In this paper, we derive new, nearly optimal bounds for the Gaussian approximation to scaled averages of n independent high-dimensional centered random vectors X1, . . . , Xn over the class of rectangles in the case when the covariance matrix of the scaled average is non-degenerate. In the case...

Time-consistency is a key feature of many important policy problems, such as those relating to optimal fiscal policy and optimal monetary policy. It is also important for private-sector decision-making through mechanisms such as quasi-geometric discounting. These problems are generally solved...

Rich data generating mechanisms are ubiquitous in this age of information and require complex statistical models to draw meaningful inference. While Bayesian analysis has seen enormous development in the last 30 years, benefitting from the impetus given by the successful application of Markov...

In this paper, I examine the welfare consequences of conventional approximation methods in business cycle analysis: the log-linear approximation of model dynamics and the second-order approximation of social welfare. In a canonical New Keynesian model, the approximation around the deterministic...

Time-consistency is a key feature of many important policy problems, such as those relating to optimal fiscal policy and optimal monetary policy. It is also important for private-sector decision-making through mechanisms such as quasi-hyperbolic discounting. These problems are generally solved...

We develop approximate estimation methods for exponential random graph models (ERGMs), whose likelihood is proportional to an intractable normalizing constant. The usual approach approximates this constant with Monte Carlo simulations, however convergence may be exponentially slow. We propose a...

Over the most recent couple of years, the Internet of Things and other empowering innovations have been logically utilized for digitizing the vegetable supply chain (VSC). Background: The unpredictable examples and complexity inserted in enormous data dimensions present a test for an orderly...

We present an accurate and easy-to-compute approximation of the transition probabilities and the associated Arrow-Debreu (AD) prices for the Inhomogeneous Geometric Brownian Motion (IGBM) model for interest rates, default intensities or volatilities. Through this procedure, dubbed exponent...

This paper introduces a nonlinear certainty equivalent approximation method for dynamic stochastic problems. We first use a novel, stable and efficient method for computing the optimal policy functions for deterministic dynamic optimization problems, and then use them as certainty-equivalent...

A principal distinction of neural network based methods of approximation from conventional methods is a hidden inside algorithmic function, which is defined by the neural network topology and is enough sophisticated to make appropriate fitting process. There is a new construction named...

Chapter 1. Retailer’s Optimal Ordering Policy under Supplier Credits when Demand is Fuzzy and Cloud Fuzzy -- Chapter 2. An Application of PSO to Study joint policies of an Inventory Model with Demand Sensitive to Trade credit and Selling price while Deterioration of item being controlled using...

This paper introduces a nonlinear certainty-equivalent approximation method for dynamic stochastic problems. We first introduce a novel, stable, and efficient method for computing the decision rules in deterministic dynamic economic problems. We use the results as nonlinear and global...