This series was first started in the June 78 issue of Online Review. Here we focus on BLAISE, the service operated by the British Library.
The British Library Automated Information Service (BLAISE) is a new name in the library and information world. It is in essence an on‐line library‐housekeeping and information…
Abstract
The British Library Automated Information Service (BLAISE) is a new name in the library and information world. It is in essence an on‐line library‐housekeeping and information service which is being created by the British Library based on established information retrieval software. The Library will use the ELHILL IHC software package which is run by the National Library of Medicine in the USA. BLAISE will provide on‐line access to the MEDLARS and the MARC files with access to the former in the spring of 1977 on an IBM 370 computer at a bureau in Harlow, Essex.
Downloading and uploading offer labour‐saving advantages and are now accepted as useful options in online searching. All aspects are here considered, from recent technical…
Abstract
Downloading and uploading offer labour‐saving advantages and are now accepted as useful options in online searching. All aspects are here considered, from recent technical advances, applications and legal attitudes. There is also a review of current software for downloading. Recent developments mean a trend to higher internal memory and storage capacity, and greater transmission speeds. Packages now offer access to more than one host, give maximum assistance to the user without being menu‐driven and incorporate the latest developments in artificial intelligence. Disadvantages are in the length of time involved in the process and the fact that the legal issue of copyright has not yet been finalised. Database producers have turned to licensing under contract law, but there is still need to rely on user ethics, and the need for a standard permissions form is highlighted.
Details
Keywords
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).
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
Keywords
Balira O. Konfe, Yves Cherruault and Blaise Some
To propose a new method for solving constrained global optimization problems using a method that consists of transforming a constrained global optimization problem into an…
Abstract
Purpose
To propose a new method for solving constrained global optimization problems using a method that consists of transforming a constrained global optimization problem into an unconstrained one without using any penalty coefficients.
Design/methodology/approach
Use of an unconstrained global optimization method such as the Alienor method which has been adapted for several variables.
Findings
Use of the adapted Alienor method allowed the solution of the transformed problem with little difficulty.
Research limitations/implications
Transforms the original objective function into a new one involves the introduction of some extra parameters. Cannot guarantee the convergence to a global solution of the original problem. The simple described approach, provides new possibilities.
Practical implications
No further parameters introduced in this new approach, and no conditions or hypotheses are imposed on the objective function or on the constraints.
Originality/value
New method of transforming a constrained problem into an unconstrained one, with use of proven Alienor method adapted to several variables.
Details
Keywords
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 to…
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
Keywords
Benjamin Mampassi, Bisso Saley, Blaise Somé and Yves Cherruault
To compute an optimal control of non‐linear reaction diffusion equations that are modelling inhibitor problems in the brain.
Abstract
Purpose
To compute an optimal control of non‐linear reaction diffusion equations that are modelling inhibitor problems in the brain.
Design/methodology/approach
A new numerical approach that combines a spectral method in time and the Adomian decomposition method in space. The coupling of these two methods is used to solve an optimal control problem in cancer research.
Findings
The main conclusion is that the numerical approach we have developed leads to a new way for solving such problems.
Research limitations/implications
Focused research on computing control optimal in non‐linear diffusion reaction equations. The main idea that is developed lies in the approximation of the control space in view of the spectral expansion in the Legendre basis.
Practical implications
Through this work we are convinced that one way to derive efficient numerical optimal control is to associate the Legendre expansion in time and Runge Kutta approximation. We expect to obtain general results from optimal control associated with non‐linear parabolic problem in higher dimension.
Originality/value
Coupling of methods provides a numerical solution of an optical control problem in Cancer research.