A web-based workforce management system for Sainsburys Supermarkets Ltd

Labour scheduling plays an important and critical role in Sainsburys day to day operations and profitability. The integrated workforce management solution for Sainsburys is an intelligent solution for the operational deployment of human resources, integrated business forecasting, generation and calculation of workload and staff scheduling. The workforce management technology has provided Sainsburys with a fully web-based and centralised system that produces optimised schedules for all employees satisfying the forecasted demand of work with granularity of fifteen minutes. The system is configured to respect all operational and business requirements as well as employee contractual constraints. This paper introduces the workforce management solution system designed, developed and implemented for Sainsburys. We concentrate on two modelling structures, namely the work pattern model and optimisation model, and briefly discuss the optimisation process.     

Thermal effects and band spreading in capillary electro-separation

Summary Four Capillary Electroseparation methods are distinguished. All have an ultimate efficiency limited only by axial diffusion and are in principle capable of achieving 10⁶ plates in <1 hour.The main limitation to performance arises from Ohmic heating of the electrolyte. While forced convection at 10ms^–1 is recommended to keep tubes cool, the parabolic temperature profile within the electrolyte limits the tube bore which can be used. A simple limiting expression is derived: (d_c/m)³ (E/kV m^–1)³ (c/mol dm^–3) <3.3×10⁹.Values of constants underlined     

Consequences of sample size, variable selection, and model validation and optimisation, for predicting classification ability from analytical data

This article discusses problems of validating classification models especially in datasets where sample sizes are small and the number of variables is large. It describes the use of percentage correctly classified (%CC) as an indicator for success of a classification model. For small datasets, %CC should not be used uncritically and its interpretation depends on sample size. It illustrates the use of a common classification method, discriminant partial least squares (D-PLS) on a randomly generated dataset of 200 samples and 200 variables.

An aim of the classifier is to determine whether the null hypothesis (there is no distinction between two classes) can be rejected. Autoprediction gives an 84.5% CC. It is shown that, if there is variable selection, it must be performed independently on the training set to obtain a CC close to 50% on the test set; otherwise, over-optimistic and false conclusions can be reached about the ability to classify samples into groups.

Finally, two aims of determining the quality of a model are frequently confused, namely optimisation (often used to determine the most appropriate number of components in a model) and independent validation; to overcome this, the data should be split into three groups.

There are often difficulties with model building if validation and optimisation have been done on different groups of samples, especially using iterative methods, each group being modelled using properties, such as a different number of components or different variables.     

Hybrid genetic algorithm–tabu search approach for optimising multilayer optical coatings

Constructing multilayer optical coatings (MOCs) is a difficult large-scale optimisation problem due to the enormous size of the search space. In the present paper, a new approach for designing MOCs is presented using genetic algorithms (GAs) and tabu search (TS). In this approach, it is not necessary to specify how many layers will be present in a design, only a maximum needs to be defined. As it is generally recognised that the existence of specific repeating blocks is beneficial for a design, a specific GA representation of a design is used which promotes the occurrence of repeating blocks. Solutions found by GAs are improved by a new refinement method, based on TS, a global optimisation method which is loosely based on artificial intelligence. The improvements are demonstrated by creating a visible transmitting/infrared reflecting filter with a wide variety of materials.     

Optimisation of the chlorthalidone chiral separation by capillary electrochromatography using an achiral stationary phase and cyclodextrin in the mobile phase

The separation of chlorthalidone enantiomers in capillary electrochromatography on an achiral stationary phase when adding a chiral selector, hydroxypropyl-β-cyclodextrin, to the mobile phase, was optimised. The goal was to investigate the feasibility of modelling retention times and resolution when during the optimisation procedure regular replacement of columns is required due to their fragility. Therefore, it is essential that the packing procedure delivers reproducible columns. The optimisation of an existing chlorthalidone separation was chosen as case study. The influence of two factors, chiral selector concentration and organic modifier content, on the responses was modelled. The experiments performed prior to modelling were defined by a central composite design. Results on different columns, obtained under identical experimental conditions, were found comparable and thus modelling was possible in situations where several columns were required to complete a design. A second-order polynomial model was built for both responses. Optimal separations were also predicted using Derringer’s desirability functions. The optimum was found at 33 mM cyclodextrin and 16% (v/v) acetonitrile on two types of columns (with different packing times) leading to a strong reduction in analysis time for an equally good separation compared to the initial conditions. Measured and predicted responses were found comparable, indicating that acceptable models were obtained.     

New approach to linear gradient elution used for optimisation in reversed-phase liquid chromatography

A new mathematical treatment concerning the gradient elution in reversed-phase liquid chromatography when the volume fraction psi of an organic modifier in the water-organic mobile phase varies linearly with time is presented. The experimental ln k versus psi curve, where k is the retention factor under isocratic conditions in a binary mobile phase, is subdivided into a finite number of linear portions and the solute gradient retention time tR is calculated by means of an analytical expression arising from the fundamental equation of gradient elution. The validity of the proposed analytical expression and the methodology followed for the calculation of tR was tested using eight catechol-related solutes with mobile phases modified by methanol or acetonitrile. It was found that in all cases the accuracy of the predicted gradient retention times is very satisfactory because it is the same with the accuracy of the retention times predicted under isocratic conditions. Finally, the above method for estimating gradient retention times was used in an optimisation algorithm, which determines the best variation pattern of psi that leads to the optimum separation of a mixture of solutes at different values of the total elution time.     

Application of a dynamic method of minimisation in the study of reaction surfaces

This paper describes the application of Snyman's dynamic minimisation method to a fitted potential surface of H₃. Comparisons are made with conventional algorithms. A method is described to extend Snyman's method so that it will find only a particular kind of stationary point. It is emphasized that this method enables saddle points to be found without having to resort to approaches based on trial and error.     

Optimisation of a flow injection system with electrochemical detection using the desirability function: Application to the determination of hydroquinone in cosmetics

A procedure is proposed in which the determination of hydroquinone using a flow injection system with electrochemical detection is described. Size and coefficient of variation of the signal are optimised by a desirability function and a central composite design. The robustness of the optimum reached in the optimisation step is evaluated by means a Plackett-Burman design. The optimised FIA system is able to determine hydroquinone with a minimum detectable net concentration of 10 μg l⁻¹ with a false positive probability of 0.05 and a false negative probability less than 0.05. In samples of bleaching cream, the proposed procedure has a recovery of 102.2% with standard deviation of 4.4% and a relative error of 6.2%.     

An Ant Colony Optimisation algorithm for solving the asymmetric traffic assignment problem

In this paper we propose an Ant Colony Optimisation (ACO) algorithm for defining the signal settings on urban networks following a local approach. This consists in optimising the signal settings of each intersection of an urban network as a function only of traffic flows at the accesses to the same intersection, taking account of the effects of signal settings on costs and on user route choices. This problem, also known as Local Optimisation of Signal Settings (LOSS), has been widely studied in the literature and can be formulated as an asymmetric assignment problem. The proposed ACO algorithm is based on two kinds of behaviour of artificial ants which allow the LOSS problem to be solved: traditional behaviour based on the response to pheromones for simulating user route choice, and innovative behaviour based on the pressure of an ant stream for solving the signal setting definition problem. Our results on real-scale networks show that the proposed approach allows the solution to be obtained in less time but with the same accuracy as in traditional MSA (Method of Successive Averages) approaches.     

Tiling solutions for optimal biological sensing

Biological systems, from cells to organisms, must respond to the ever-changing environment in order to survive and function. This is not a simple task given the often random nature of the signals they receive, as well as the intrinsically stochastic, many-body and often self-organized nature of the processes that control their sensing and response and limited resources. Despite a wide range of scales and functions that can be observed in the living world, some common principles that govern the behavior of biological systems emerge. Here I review two examples of very different biological problems: information transmission in gene regulatory networks and diversity of adaptive immune receptor repertoires that protect us from pathogens. I discuss the trade-offs that physical laws impose on these systems and show that the optimal designs of both immune repertoires and gene regulatory networks display similar discrete tiling structures. These solutions rely on locally non-overlapping placements of the responding elements (genes and receptors) that, overall, cover space nearly uniformly.