Estimating intertemporal elasticity of substitution of labor supply for married women in Russia

This paper provides an econometric analysis of the labor supply function of married women in Russia based on data from RLMS HSE and methodology from the work (Heckman, MaCurdy, 1980), in which decisions about entering the labor market and the intensity of work are made within a dynamic optimization problem. It is shown that the husband’s leisure and the number of children living in the household have a negative effect on the woman’s hours worked. The estimate of the Frisch elasticity of labor supply with respect to wages lies near 0.16.

Resolution of Dynamic Optimization Problems Constrained by the Fraction Penalty Method

This article discusses the application of fractional penalty method to solve dynamic optimization problem with state constraints. The main theories supporting the use of the method are described in some theorem and corollary. The theorems give sufficient conditons for the application of the method. Therefore, if all conditions mentioned in the theorems are met then the resulted solution will converge to the analytic solution. In addition, there are some examples to support the theory. The numerical simulation shows that the accuracy of the method is quite good. Hence, this method can play a role as an alternative method for solving dynamic optimization problem with state constrints.

Swarm algorithms in dynamic optimization problem of reactive power compensation units control

Optimization of a power supply system is one of the main directions in power engineering research. The reactive power compensation reduces active power losses in transmission lines. In general, researches devoted to allocation and control of the compensation units consider this issue as a static optimization problem. However, it is dynamic and stochastic optimization problem that requires a real-time solution. To solve the dynamic optimization NP-hard problem, it is advisable to use Swarm Intelligence. This research deals with the problem of the compensation units power control as a dynamic optimization problem, considering the possible stochastic failures of the compensation units. The Particle Swarm Optimization and the Bees Algorithm were applied to solve it to compare the effectiveness of these algorithms in the dynamic optimization of a power supply system.

Influence of Sea Current on Stabilization of Moments and Forces in Risers

One of the important aspects in the design of floating, production, storage, and offloading (FPSO) systems is to ensure a fairly constant load on risers despite the base motion caused by sea waves. The paper presents the authors’ own formulation of the finite segment method for dynamic analysis of risers and its application to the solution of a dynamic optimization problem. This task consists in defining vertical displacements of the top of the riser which compensate horizontal movements of the vessel or platform caused by sea waves. Compensation involves stabilizing the bending moment in the risers or the force in the connection of the riser and the wellhead. The model takes into account the influence of the sea by means of Morison equations. Different sea current profiles are considered. Calculation of vertical displacements of the top of the riser is carried out in order to stabilize the force or the bending moment for a defined function of horizontal displacements of the riser.

Modeling On-Site Combined Heat and Power Systems Coupled to Main Process Operation

Many production processes work with on-site Combined Heat and Power (CHP) systems to reduce their operational cost and improve their incomes by selling electricity to the external grid. Optimal management of these plants is key in order to take full advantage of the possibilities offered by the different electricity purchase or selling options. Traditionally, this problem is not considered for small cogeneration systems whose electricity generation cannot be decided independently from the main process production rate. In this work, a non-linear gray-box model is proposed in order to deal with this dynamic optimization problem in a simulated sugar factory. The validation shows that with only 52 equations, the whole system behavior is represented correctly and, due to its structure and small size, it can be adapted to any other production process working along a CHP with the same plant configuration.

A Two-Stage Method for Parameter Identification of a Nonlinear System in a Microbial Batch Process

This paper deals with the parameter identification of a microbial batch process of glycerol to 1,3-propanediol (1,3-PD). We first present a parameter identification model for the excess kinetics of a microbial batch process of glycerol to 1,3-PD. This model is a nonlinear dynamic optimization problem that minimizes the sum of the least-square and slope errors of biomass, glycerol, 1,3-PD, acetic acid, and ethanol. Then, a two-stage method is proposed to efficiently solve the presented dynamic optimization problem. In this method, two nonlinear programming problems are required to be solved by a genetic algorithm. To calculate the slope of the experimental concentration data, an integral equation of the first kind is solved by using the Tikhonov regularization. The proposed two-stage method could not only optimally identify the model parameters of the biological process, but could also yield a smaller error between the measured and computed concentrations than the single-stage method could, with a decrease of about 52.79%. A comparative study showed that the proposed two-stage method could obtain better identification results than the single-stage method could.

An HJB approach to a general continuous-time mean-variance stochastic control problem

A general continuous mean-variance problem is considered for a diffusion controlled process where the reward functional has an integral and a terminal-time component. The problem is transformed into a superposition of a static and a dynamic optimization problem. The value function of the latter can be considered as the solution to a degenerate HJB equation either in the viscosity or in the Sobolev sense (after a regularization) under suitable assumptions and with implications with regards to the optimality of strategies. There is a useful interplay between the two approaches – viscosity and Sobolev.