Stochastic Maximum Principle for Optimal Advertising Models with Delay and Non-Convex Control Spaces

In this paper we study optimal advertising problems that model the introduction of a new product into the market in the presence of carryover effects of the advertisement and with memory effects in the level of goodwill. In particular, we let the dynamics of the product goodwill to depend on the past, and also on past advertising efforts. We treat the problem by means of the stochastic Pontryagin maximum principle, that here is considered for a class of problems where in the state equation either the state or the control depend on the past. Moreover the control acts on the martingale term and the space of controls U can be chosen to be non-convex but now the space of controls U can be chosen to be non-convex. The maximum principle is thus formulated using a first-order adjoint Backward Stochastic Differential Equations (BSDEs), which can be explicitly computed due to the specific characteristics of the model, and a second-order adjoint relation.

The Accelerated Expansion of the Universe in the Light of the Maximum Ordinality Principle

The main aim of the paper is to present (and at the same time offer) a differ-ent perspective for the analysis of the accelerated expansion of the Universe. A perspective that can surely be considered as being “in parallel” to the tradition-al ones, such as those based, for example, on the hypotheses of “Dark Matter” and “Dark Energy”, or better as a “com-possible” perspective, because it is not understood as being “exclusive”. In fact, it is an approach that, when con-firmed by experimental results, always keeps its validity from an “operative” point of view. This is because, in analogy to the traditional perspectives, on the basis of Popper’s Falsification Principle the corresponding “Generative” Logic on which it is based has not the property of the perfect induction. The basic difference then only consists in the fact that the Evolution of the Universe is now modeled by considering the Universe as a Self-Organizing System, which is thus analyzed in the light of the Maximum Ordinality Principle.

Three-Drug Therapies in Psychiatry in the Light of the Maximum Ordinality Principle and the Explicit Solution to the “Three-Body Problem”—D.D. 23 Luglio 2023, Tempo Ordinario (3.00 e 10.20)

The present paper aims at showing the possible adoption in Psychiatry of a general methodology finalized to prescribe the most appropriate Therapy based on the knowledge of its correlative effects in advance, instead of recognizing them ex post. The specific case here considered is the “bipolar disorder”, in which the adoption of three different drugs is the most common practice, although with a possible differentiation between the prescription in the morning and in the evening, respectively. Thus, the proposed methodology will consider the Ordinal Interactions between the various drugs by evaluating their combined effects, which will result as being not a simple additive “sum”, because they are evaluated on the basis of the Maximum Ordinality Principle (MOP) and, in addition, in Adherence to the Explicit Solution to the “Three-Body Problem”. In this way the Methodology here proposed is able to suggest how to account for the synergistic effects of the various drugs, especially when the latter are characterized by different concentrations and, at the same time, by generally different half-lives respectively.

Solution to the “Three-Body Problem” in the Light of the Maximum Ordinality Principle, as a “Suggestion” for a Ri-Orientation of the Present Scientific Perspective in “Favor” of the “Irreducible Quality”

This paper presents the Solution to the “Three-body Problem” in the Light of the Maximum Ordinality Principle. In the first part, however, it starts with the Solution to the Solar System, made up of “11 Bodies”. This is because, in such a context, the “Three-body Problem” can be analyzed in its all descriptive possibilities. Nonetheless, the paper also presents the Solution to the “Three-body Problem” with reference to Systems totally independent from the Solar System, such as, for example, the “Triple Stars” and the “Triple Galaxies”. In this way, the paper offers a sufficiently complete framework concerning the Solution to the “Three-body Problem”, always in the Light of the Maximum Ordinality Principle, described in detail in Appendix A.

Generativity of Self-Organizing Processes and Their Correlative Description in Terms of a Formal Language of Meta-Ordinal Generative Nature, in the Light of the Maximum Ordinality Principle and the Explicit Solution to the “Three-Body Problem”

The main objective of this paper is to demonstrate that the internal processes of Self-Organizing Systems represent a unique and singular process, characterized by their specific generativity. This process can be modeled using the Maximum Ordinality Principle and its associated formal language, known as the “Incipient” Differential Calculus (IDC).

A RISK-SENSITIVE STOCHASTIC MAXIMUM PRINCIPLE FOR OPTIMAL CONTROL OF JUMP DIFFUSIONS AND ITS APPLICATIONS

A stochastic maximum principle for the risk-sensitive optimal control prob- lem of jump diffusion processes with an exponential-of-integral cost functional is derived assuming that the value function is smooth, where the diffusion and jump term may both depend on the control. The form of the maximum principle is similar to its risk-neutral counterpart. But the adjoint equations and the maximum condition heavily depend on the risk-sensitive parameter. As applications, a linear-quadratic risk-sensitive control problem is solved by using the maximum principle derived and explicit optimal control is obtained.

LOWER INEQUALITIES OF HEAT SEMIGROUPS BY USING PARABOLIC MAXIMUM PRINCIPLE

Using parabolic maximum principle, we apply the analytic method to obtain lower comparison inequalities for non-negative weak supersolutions of the heat equation associated with a regular strongly p-local Dirichlet form on the abstract metric measure space. As an application we obtain lower estimates for heat kernels on some Riemannian manifolds.

Maximum modulus principle estimates for one dimensional fractional diffusion equation

We present scheme I for solving one-dimensional fractional diffusion equation with variable coefficients based on the maximum modulus principle and two Grunwald approxima- tions. Scheme II is obtained by using classic Crank-Nicolson approximations in order to improve the time convergence. Schemes are proved to be unconditionally stable and second-order accuracy in spatial grid size for the problem with order of fractional derivative belonging to [（√17- 1）/2, 2] using the maximum modulus principle. A numerical example is given to confirm the theoretical analysis result.

Maximum principle for anticipated recursive stochastic optimal control problem with delay and Lvy processes

In this paper, we study the stochastic maximum principle for optimal control prob- lem of anticipated forward-backward system with delay and Lovy processes as the random dis- turbance. This control system can be described by the anticipated forward-backward stochastic differential equations with delay and L^vy processes （AFBSDEDLs）, we first obtain the existence and uniqueness theorem of adapted solutions for AFBSDEDLs; combining the AFBSDEDLs＇ preliminary result with certain classical convex variational techniques, the corresponding maxi- mum principle is proved.

A Mean-Field Stochastic Maximum Principle for Optimal Control of Forward-Backward Stochastic Differential Equations with Jumps via Malliavin Calculus

This paper considers a mean-field type stochastic control problem where the dynamics is governed by a forward and backward stochastic differential equation (SDE) driven by Lévy processes and the information available to the controller is possibly less than the overall information. All the system coefficients and the objective performance functional are allowed to be random, possibly non-Markovian. Malliavin calculus is employed to derive a maximum principle for the optimal control of such a system where the adjoint process is explicitly expressed.

The Maximum Principle for Fully Coupled Forward-backward Stochastic Control System

The maximum principle for fully coupled forward-backward stochastic control system in the global form is proved, under the assumption that the forward diffusion coefficient does not contain the control variable, but the control domain is not necessarily convex.

Increasing of Resistance and Resilience of an Urban System against Calamities in the Light of the Maximum Ordinality Principle

The present paper aims at showing how it is possible to requalify the structures of an urban system, in order to increase its resistance and its correlative resilience, against natural calamities (earthquakes, hurricanes, etc.), by adopting as reference criterion the Maximum Ordinality Principle (MOP). In this sense, the paper opens a radically new perspective in this field. In fact, the village assumed as a case study was modelled as a Self-Organizing System. This is because, although the village is usually considered as being solely made of buildings, streets, places and so on, in reality it has been conceived, planned and realized by human beings during several centuries. In addition, the people who actually leave in such an urban center, systematically deal with its maintenance, in order to possibly increase its functionality. This justifies the assumption of the village as being a Self-Organizing System and, consequently, it has been analyzed in the light of the MOP, which represents a valid reference principle for analyzing both “non-living”, “living” and “conscious” self-organizing systems.

Quality Evaluation and Its Application to Surface Water Ecosystem Based on Maximum Flux Principle

Based on the maximum flux principle(MFP),a water quality evaluation model for surface water ecosystem is presented by using self-organization map(SOM) neural network simulation algorithm from the aspect of systematic structural evolution.This evaluation model is applied to the case of surface water ecosystem in Xindu District of Chengdu City in China.The values reflecting the water quality of five cross-sections of the system at different developing stages are obtained,with stable values of 1.438,2.952,1.869,2.443 and 2.479,respectively.The simulation also indicates that the larger the value,the more serious the water pollution.Furthermore,a classification graph is given to reflect the evolution of structural pattern.The combination of MFP and SOM neural network reveals the formation of different structural patterns in the system during the interaction of internal components.It is shown that a dominant pattern is finally reserved,which starts from a variety of combination patterns for a time period.The results agree with those from traditional evaluation methods,which indicates that the proposed model has high accuracy.This model embodies the evolutionary dynamic mechanisms and characteristics of temporal and spatial changes,which helps to guide the prediction of water quality status of surface water ecosystem.

A modified method to calculate reliability index using maximum entropy principle

Routine reliability index method, first order second moment (FOSM), may not ensure convergence of iteration when the performance function is strongly nonlinear. A modified method was proposed to calculate reliability index based on maximum entropy (MaxEnt) principle. To achieve this goal, the complicated iteration of first order second moment (FOSM) method was replaced by the calculation of entropy density function. Local convergence of Newton iteration method utilized to calculate entropy density function was proved, which ensured the convergence of iteration when calculating reliability index. To promote calculation efficiency, Newton down-hill algorithm was incorporated into calculating entropy density function and Monte Carlo simulations (MCS) were performed to assess the efficiency of the presented method. Two numerical examples were presented to verify the validation of the presented method. Moreover, the execution and advantages of the presented method were explained. From Example 1, after seven times iteration, the proposed method is capable of calculating the reliability index when the performance function is strongly nonlinear and at the same time the proposed method can preserve the calculation accuracy; From Example 2, the reliability indices calculated using the proposed method, FOSM and MCS are 3.823 9, 3.813 0 and 3.827 6, respectively, and the according iteration times are 5, 36 and 10 6 , which shows that the presented method can improve calculation accuracy without increasing computational cost for the performance function of which the reliability index can be calculated using first order second moment (FOSM) method.

OPTIMAL FEED STRATEGY FOR FED-BATCH GLYCEROL FERMENTATION DETERMINED BY MAXIMUM PRINCIPLE

Optimal glucose feed strategy for glycerol fed-batch fermentation was investigated by Pontryagin’s maximum principle to maximize the final glycerol yield. The problem was solved by a nonsingular control approach by selecting the culture volume as the control variable, then the general optimal feed profile was numerically determined.

A MAXIMUM PRINCIPLE FOR DISTRIBUTED PARAMETER SYSTEMS WITH MIXED PHASE-CONTROL CONSTRAINTS ANDENDPOINT CONSTRAINTS

This paper considered the optimal control problem for distributed parameter systems with mixed phase-control constraints and end-point constraints. Pontryagin's maximum principle for optimal control are derived via Duboviskij-Milujin theorem.

High-order maximum-principle-preserving and positivity-preserving weighted compact nonlinear schemes for hyperbolic conservation laws

In this paper,the maximum-principle-preserving(MPP)and positivitypreserving(PP)flux limiting technique will be generalized to a class of high-order weighted compact nonlinear schemes(WCNSs)for scalar conservation laws and the compressible Euler systems in both one and two dimensions.The main idea of the present method is to rewrite the scheme in a conservative form,and then define the local limiting parameters via case-by-case discussion.Smooth test problems are presented to demonstrate that the proposed MPP/PP WCNSs incorporating a third-order Runge-Kutta method can attain the desired order of accuracy.Other test problems with strong shocks and high pressure and density ratios are also conducted to testify the performance of the schemes.

Surface Elevation Distribution of Sea Waves Based on the Maximum Entropy Principle

A probability density function of surface elevation is obtained through improvement of the method introduced by Cieslikiewicz who employed the maximum entropy principle to investigate the surface elevation distribution. The density function can be easily extended to higher order according to demand and is non-negative everywhere, satisfying the basic behavior of the probability, Moreover because the distribution is derived without any assumption about sea waves, it is found from comparison with several accepted distributions that the new form of distribution can be applied in a wider range of wave conditions, In addition, the density function can be used to fit some observed distributions of surface vertical acceleration although something remains unsolved.

Necessary Maximum Principle of Stochastic Optimal Control with Delay and Jump Diffusion

In this paper, we have studied the necessary maximum principle of stochastic optimal control problem with delay and jump diffusion.

A MAXIMUM PRINCIPLE APPROACH TO STOCHASTIC H_2/H_∞ CONTROL WITH RANDOM JUMPS

A necessary maximum principle is given for nonzero-sum stochastic Oltterential games with random jumps. The result is applied to solve the H2/H∞ control problem of stochastic systems with random jumps. A necessary and sufficient condition for the existence of a unique solution to the H2/H∞ control problem is derived. The resulting solution is given by the solution of an uncontrolled forward backward stochastic differential equation with random jumps.