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Decomposition of several variables functions by means of functions of one variable was a fundamental problem, studied by mathematicians, and the specially by KOLMOGOROV school. This question is closely connected with optimization and optimal control and with multiple integrals calculus. These problems have been investigated by Professor Y. Cherruault and colleagues, using the ALIENOR method, which is based on α‐dense curves. The decomposition method of Adomian can be coupled with global optimization for solving optimal control problems. Aim is to calculate multiple integrals by a special decomposition of the function using an orthonormal basis of functions. Presents also new methods for approximating a n‐variables function by means of the sum of product of n functions only depending on a single variable. Applications to multi‐variables optimization problems and optimal control system are described.

In this paper our objective is to show how to approach the solution of any first order partial differential equation (p.d.e.), using Adomian decompositon method and α‐dense curves. Indicates that this method is perfectly adapted to the solution of such equations and especially in the nonlinear case. The results are of particular importance in biomedicine and biocybernetics.

The purpose of this paper is to describe a general method for solving all problems arising in industrial processes and more generally in operational research.

The paper's aim is to present a new method based on α‐dense curves first developed at the beginning of the 1980s by Yves Cherruault and Arthur Guillez. This technique allows to solve all problems of operational research in a simple way. For instance, industrial problems leading to optimization or optimal control problems can be easily and precisely solved by this very general technique. The main idea consists in expressing n variables by means of a single one.

This new method, based on “alpha‐dense curves” allows to express n variables in function of a single variable. One of the most important applications is related to global optimization. Multivariable optimization problems can be quickly and easily solved, even for great numbers of variables and for integer or boolean variables. Every problem (linear or nonlinear) coming from operational research or from industry becomes simple to solve in a very short time on micro‐calculators.

This method is deduced from the original works of Yves Cherruault et al. of MEDIMAT laboratory. The reducing transformations were initiated at the beginning of the 1980s by Yves Cherruault and Arthur Guillez. Then they were generalized by the notion of α‐dense curves. A lot of applications were derived covering entirely the operational research and a part of functional analysis.

The Alienor method, based on α ‐dense curves, has been developed by Yves Cherruault and collaborators, to solve optimization problems. It can be coupled with the decomposition method of Adomian to solve optima control problems also. But α ‐dense curves can be used in many other problems. Gives an application of α ‐dense curves for calculating multiple integrals by means of simple integrals.

Aim's to show how to approach the solution for a class of first order p.d.e. using Adomian decomposition method. Discusses the generalities of the method and α‐dense curves. Outlines the new approach and provides applications of its use.

Describes the use of the decomposition method for solving the differential system governing the interaction between two species, based on the Lotka‐Volterra model. The Alienor method is applied for identifying the parameters of the model, which are the intrinsic rates of natural increase of the different species and their interaction coefficients.

The Alienor technique for global optimisation is described. The method is deterministic and uses the approximate properties of Archimedes' spirals, reducing n variables to a single one. It is shown that Monte Carlo methods are less efficient than Alienor, they need more computing time and convergence is not absolutely guaranteed. The application of the Alienor technique to many concrete problems is discussed.

Aims to study direct identification of general linear compartmental systems by means of (n−2) compartmental measures. This is based on two main results.

The first result presented is related to the existence and uniqueness of identification exchange parameters in linear compartmental systems by using a direct method with less restrictive assumptions. A second result given, permits us to show that (n−2) observations are sufficient to identify the compartmental systems.

This research study describes a method which shows that in an open linear compartmental systems there exists an energy dissipation from compartmental 1 to the systems exterior. An explicit relationship between the dissipated energy and the exchange parameters was established. The results are probably perfectible and are optimal for n=3, where only an observable compartment is needed.

The identification of exchange parameters is easily obtained by using the matrix of the elementary masses and by solving a linear algebraic system. Among the open problems in compartmental analysis is the problem of minimizing the observable compartments which is studied in this paper.

The study is based on the original work of Yves Cherruault who has already presented methods for proving that a bicompartmental systems is uniquely identified. He has generalised his method for n‐compartments.

To prove two results. Namely that if in a linear homogeneous bicompartmental system one compartment is measured then it is indefinable. The second one is related to the identification of non‐linear compartmental models by mean of a linear method.

The first result is generalized to linear non‐homogeneous bicompartmental systems of Michaelis‐Menten (M‐M systems). The second one is related to the identification of a non‐linear compartmental model. The obtained linear system is not homogeneous and must be generalized to nonhomogeneous systems. Then the Jacobian matrix associated to the M‐M systems is identified and the M‐M parameters are deduced by continuity from the Cauchy problem's solution.

Both stated results were proved and any open linear bicompartmental system whether homogeneous or not, of the type I is identifiable.

In compartmental analysis the exchange hypothesis allows us to represent a model of any phenomenon depending on time. Many phenomena require “the enzyme reactions” leading to the M‐M laws. These laws assert that the quantity of matter going from compartment can be defined and M‐M constants prescribed. This research considers both homogeneous and nonhomogeneous systems cases.

Contributes to the identification of linear and non‐linear bicompartmental systems which are of biocybernetical significance.

The two proven results are new and applicable.

This paper deals with the use of the combined Adomian/Alienor methods for solving the problem of optimal cancer chemotherapy model.

The combination of the Adomian decomposition method and the Alienor reducing transformation method allows us to solve the control problem as if it were a classical one dimensional minimization problem. The mathematical model used here describes specific model based on cell‐cycle kinetics.

It was found that the goal is to maintain the number of the cancerous cells around a desired value while keeping the toxicity to the normal tissues acceptable.

Simulation results are given for illustration.

New combined approach to optimal control of cancer chemotherapy using Adomian/Alienor Methods.