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Article
Publication date: 1 May 2006

Pierre Mora

For several years now, Bordeaux's vineyards have suffered from what would appear to be an interminable crisis. Some analysts view overproduction as the cause. Others blame…

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Abstract

Purpose

For several years now, Bordeaux's vineyards have suffered from what would appear to be an interminable crisis. Some analysts view overproduction as the cause. Others blame the product Bordeaux puts out, decrying its lack of adaptation to new consumer expectations. What is true is that Bordeaux producers do not tend to spontaneously adopt a market orientation. However, faced with a dilemma that seems to be getting worse and worse, many are starting to seek their salvation in marketing. The purpose of this paper is to address these issues.

Design/methodology/approach

The present article uses a series of case studies covering regions outside of Bordeaux to find concrete answers to these questions. As a methodology, these case studies have been used to illustrate different ways to develop production and sales.

Findings

Consolidating the production, increasing the sales forces efforts, reducing the number of intermediaries between production and consumption, maintaining a niche position on the global market are one of the main findings of this paper and practical implication.

Research limitations/implications

Using case studies and not quantitative approach represents both limits of the approach and innovative methodology that permits rich comparison with local practices.

Originality/value

Analyzes a local crisis thanks to external case studies.

Details

International Journal of Wine Marketing, vol. 18 no. 2
Type: Research Article
ISSN: 0954-7541

Keywords

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Article
Publication date: 1 May 2006

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384

Abstract

Details

International Journal of Wine Marketing, vol. 18 no. 2
Type: Research Article
ISSN: 0954-7541

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Article
Publication date: 20 February 2007

J.C. Mazza, Y. Cherruault, G. Mora, B. Konfé and T. Benneouala

To use a new method based on α‐dense curved for solving problems of operational research.

Abstract

Purpose

To use a new method based on α‐dense curved for solving problems of operational research.

Design/methodology/approach

The method of global optimization (called Alienor) is used for solving problems involving integer or mixed variables. A reducing transformation using α‐dense curves allows to transforms a n‐variables problem into a problem of a single variable.

Findings

Extends the basic method valid for continuous variables to problems involving integer, Boolean or mixed variables. All problems of operational research, linear or nonlinear, may be easily solved by or technique based on α‐dense curves (filling a n‐dimensional space). Industrial problems can be quickly solved by this technique obtaining the best solutions.

Originality/value

This method is deduced from the original works of Y. Cherruault and colleagues about global optimization and α‐dense curves. It proposes new techniques for solving operational research problems.

Details

Kybernetes, vol. 36 no. 1
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 1 March 2000

A. Ziadi, Y. Cherruault and G. Mora

Some results concerning the existence of α‐dense curves with minimal length are given. This type of curves used in the reducing transformation called Alienor was invented…

Abstract

Some results concerning the existence of α‐dense curves with minimal length are given. This type of curves used in the reducing transformation called Alienor was invented by Cherruault and Guillez. They have been applied to global optimization in the following way: a multivariable optimization problem is transformed in an optimization problem depending on a single variable. Then this idea was extended by Cherruault and his team for obtaining general classes of reducing transformations having minimal properties (length of the α‐dense curves, minimization of the calculus time, etc.).

Details

Kybernetes, vol. 29 no. 2
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 1 August 2005

T. Benneouala and Y. Cherruault

To show the usefulness of the Alienor method when applied to the global optimization problems that depend on large number of variables.

Abstract

Purpose

To show the usefulness of the Alienor method when applied to the global optimization problems that depend on large number of variables.

Design/methodology/approach

The approach is to use reducing transformations. The first is due to Cherruault and the second to Mora.

Findings

It was found that the Alienor method was very efficient and reliable in solving global optimization problems of many variables. Results produced to confirm this conclusion.

Research limitations/implications

The numerical results presented showed that the Alienor method was suitable for finding global minimum even in the case of a very large number of variables. The research provides a new methodology for solving such problems.

Practical implications

No other method, we believe, can obtain such results in so short a time for hundreds or even thousands of variables.

Originality/value

The new approach relies on the originality of both the Cherruault and the Mora transformations and their earlier invention of the Alienor method.

Details

Kybernetes, vol. 34 no. 7/8
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 1 August 2005

Balira O. Konfe, Yves Cherruault, Blaise Some and Titem Benneouala

This paper presents an efficient algorithm for solving general constrained optimization problems that arise in operational research (OR).

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596

Abstract

Purpose

This paper presents an efficient algorithm for solving general constrained optimization problems that arise in operational research (OR).

Design/methodology/approach

An unified approach is accomplished by converting the constrained optimization problem into an unconstrained one and by using Alienor method coupled to the new optimization preserving operator* (OPO*) technique for the resolution.

Findings

A new algorithm for solving general constrained optimization problems with continuous objective function contributes to research in this area and in particular, to applications to OR.

Research limitations/implications

Some improvements could probably be obtained at calculation time. We will in future work, develop an adaption of these methods and techniques to optimization problems with mixed variables or with integer and Boolean variables.

Practical implications

The new algorithm can be advantageously compared with other methods such as generalized reduced gradient. Small‐sized numerical examples are given.

Originality/value

A new algorithm is given which guarantees a global optimal solution is easily obtained in all cases.

Details

Kybernetes, vol. 34 no. 7/8
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 20 February 2007

G. Mora and Y. Cherruault

To use α‐dense curves for solving an optimization problem with constraints involving integer variables.

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162

Abstract

Purpose

To use α‐dense curves for solving an optimization problem with constraints involving integer variables.

Design/methodology/approach

α‐dense curves are curves in Rn depending on a single variable able to approximate a compact KRn with precision α. It is proposed α‐dense curves allowing to obtain all integer points of a compact domain in Rn. This transformation allows to transform the functional into a new function depending on a single variable. Then we can calculate the global optimum of the functional.

Findings

Alienor method invented by Y. Cherruault allows to find global minimum of n‐continuous variables functions. Here, α‐dense curves are extended to problems involving integer variables. The curves pass through all points having integer coordinates and belonging to the compact domain. By this method integer programming (nonlinear) problems arising in operational research have been easily and exactly solved.

Originality/value

It is the first time the technique based on α‐dense curves to optimization problems with integer variables are extended. This approach is totally original and allows to solve very easily and fastly nonlinear optimization problems.

Details

Kybernetes, vol. 36 no. 2
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 1 August 2005

Balira O. Konfe, Yves Cherruault, Blaise Some and Titem Benneouala

To introduce Optimization‐Preserving‐Operators (O‐P‐Os), which are operators that are defined on classes of real functions that depend on a single variable, and allow us…

Abstract

Purpose

To introduce Optimization‐Preserving‐Operators (O‐P‐Os), which are operators that are defined on classes of real functions that depend on a single variable, and allow us to eliminate local optima and to preserve global optima.

Design/methodology/approach

Outline a new method to build O‐P‐Os. These are introduced as O‐P‐O* and lead to a new approach for solving global optimization problems.

Findings

It was found that classical discretization methods for obtaining optimum of one variable function was too time‐consuming. The simple method introduced provided solutions to the test functions chosen as examples. The solutions were provided in a short time.

Research limitations/implications

Provides new tools for mathematical programming and in particular the global optimization problems. The O‐P‐O* introduced innovative technique for solving such problems.

Practical implications

O‐P‐O* produces solutions to global optimization problems in a much improved time. The algorithm derived, and the steps for its operation proved on implementation, the efficiency of the new method. This was demonstrated by numerical results for selected functions obtained using microcomputer systems.

Originality/value

Provides new way of solving global optimization problems.

Details

Kybernetes, vol. 34 no. 7/8
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 1 August 2005

G. Mora, Y. Cherruault and J.I. Ubeda

To introduce an algorithm to solve inequalities defined by real functions on a certain compact set D of a general metric space (E, D). The device is based on α‐dense curves.

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218

Abstract

Purpose

To introduce an algorithm to solve inequalities defined by real functions on a certain compact set D of a general metric space (E, D). The device is based on α‐dense curves.

Design/methodology/approach

The solution of inequalities using α‐dense curves and also an approach to a global optimization technique, similarly obtained to that of the inequalities.

Findings

A new method is presented. The algorithm for solving inequalities is described which is based on a proven result. Inequalities of n‐variable dependence are reduced by transformation using α‐dense curves.

Research limitations/implications

The research is a continuation of studies that resulted in a new method called Alienor for solving global optimization problems associated with multi‐variable functions.

Originality/value

Based on earlier research by the authors α‐dense curves have been used which allow the transformation of a n‐variables global optimization problem into a one‐variable global one. This paper gives a new method for quickly solving the one‐variable problem.

Details

Kybernetes, vol. 34 no. 7/8
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 1 March 1999

Gaspar Mora and Yves Cherruault

Most of the known optimization methods for a given continuous function f defined on a compact set H = Πi=1,..,n[ai,bi] require strong conditions on f. In the early 1980s…

Abstract

Most of the known optimization methods for a given continuous function f defined on a compact set H = Πi=1,..,n[ai,bi] require strong conditions on f. In the early 1980s, Cherruault proposed a method, called ALIENOR which was able to reduce the multidimensional optimization problem to another one‐dimensional optimization: the optimization of the restriction fh* of f to some adequate α‐dense curve h into the domain H. The characterization, the generation of such curves as well as the theoretic calculation times associated with them, have been studied previously by the authors. Their consequences and the general problem concerning the error in the approximation to global minimum of f and the minimization of the error itself, that such reduction produces, will be the subject of this paper.

Details

Kybernetes, vol. 28 no. 2
Type: Research Article
ISSN: 0368-492X

Keywords

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