Assembly Line Balancing Using Genetic Algorithms with Heuristic-Generated Initial Populations and Multiple Evaluation Criteria*

We use genetic algorithms (GA) to solve the assembly line balancing (ALB) problem. Inparticular, we show how this technique can be used to generate feasible line balances, improve upon solutions obtained by other heuristics reported in the literature, and utilizeany one or more evaluation criteria that can be expressed in functional form. The procedure is demonstrated with two examples: (1) intimating the improvement of heuristic-generated ALB solutions by including them in the GA initial population, and (2) the possibility of balancing assembly lines with multiple criteria and side constraints. These examples suggest that GA can be a powerful tool in ALB. To investigate the utility of GA on single-criterion problems, an experiment is conducted that compares both the GA approach and conventional heuristics. Results indicate that the GA solutions are significantly improved over the heuristic solutions under the conditions studied. It is also found that the presence of heuristic-generated conventional solutions in the GA initial population leads to statistically preferred results.     

An asymptotic distribution-free selection procedure for a two-way layout problem

This paper deals with an asymptotic distribution-free subset selection procedure for a two-way layout problem. The treatment effect with the largest unknown value is of interest to us. The block effect is a nuisance parameter in this problem. The proposed procedure is based on the Hodges-Lehmann estimators of location parameters. The asymptotic relative efficiency of the proposed procedure with the normal means procedure is evaluated. It is shown that the proposed procedure has a high efficiency.     

Discriminant analysis of survey data

We consider the problem of the effect of sample designs on discriminant analysis. The selection of the learning sample is assumed to depend on the population values of auxiliary variables. Under a superpopulation model with a multivariate normal distribution, unbiasedness and consistency are examined for the conventional estimators (derived under the assumptions of simple random sampling), maximum likelihood estimators, probability-weighted estimators and conditionally unbiased estimators of parameters. Four corresponding sampled linear discriminant functions are examined. The rates of misclassification of these four discriminant functions and the effect of sample design on these four rates of misclassification are discussed. The performances of these four discriminant functions are assessed in a simulation study.     

A comparison of two procedures to select the best binomial population with sequential elimination of inferior populations

We compare the selection procedure of Levin and Robbins [1981. Selecting the highest probability in binomial or multinomial trials. Proc. Nat. Acad. Sci. USA 78, 4663–4666.] with the procedure of Paulson [1994. Sequential procedures for selecting the best one of k Koopman–Darmois populations. Sequential Analysis 13, 207–220.] to identify the best of several binomial populations with sequential elimination of unlikely candidates. We point out situations in which the Levin–Robbins procedure dominates the Paulson procedure in terms of the duration of the experiment, the expected total number of observations, and the expected number of failures. Because the Levin–Robbins procedure is also easier to implement than Paulson's procedure and gives a tighter guarantee for the probability of correct selection, we conclude that it holds a competitive edge over Paulson's procedure.     

Counting Young Carers in Switzerland – A Study of Prevalence

An online survey of children in school grades 4–9 (mostly aged 10–15) was conducted in order to determine the prevalence of young carers in Switzerland using a 2‐stage stratified sampling approach. 4082 respondents were drawn from 230 schools. A total of 3991 respondents were included in the analysis and of these 307 (7.7%) were identified as young carers. The population estimate of prevalence was 7.9 per cent. This suggests that there are around 38 400 young carers in school grades 4–9 in Switzerland. Extrapolating to the 9–16 age group gives a figure of almost 51 500.     

A two-stage procedure with accelerated test for selecting the best exponential population

In this article, we discuss a two-stage procedure for selecting the largest location parameter among k(k≥2) two-parameter exponential populations(or products) from an accelerated test. The accelerated test will be conducted at a higher stress level than that of normal in the second stage. under certain assumptions between parameter and stress leveL, the two-stage selection procedure, which guarantees that the probability of correct selection is at least p^*, is proposed. At the end of the paper , we present some useful tables that serve as a guide for the needed sample size in the second stage.     

A cross-national and comparative classification of in-country awareness and policy responses to ‘young carers’

The reality for many families where there is chronic illness, mental health problems, disability, alcohol or substance misuse is that children under the age of 18 are involved in caring. Many of these children – known as ‘young carers’ – will be providing regular and significant care, either episodically or over many years, often ‘hidden’ to health, social care and other welfare professionals and services. These children have most often been invisible in social policy and professional practice. What are the reasons why some countries recognize young carers as a priority for social policy while others (most) do not? What are the key factors that influence a country’s awareness and responses to these children? This article provides an original classification and analysis of country-level responses to young carers, drawing on published research, grey literature, policy documents and the authors’ extensive engagement in policy and practice networks for young carers and their families in a wide range of countries. The analysis identifies two of the key factors that influence the extent and nature of these policy responses, focusing on the importance of a reliable in-country research base and the contribution of influential national NGOs and their networks.     

Selection of the best with a preliminary test for two-parameter exponential distributions

This paper deals with the problem of selecting the best population from among k(≥ 2) two-parameter exponential populations. New selection procedures are proposed for selecting the unique best. The procedures include preliminary tests which allow the xperimenter to have an option to not select if the statistical evidence is not significant. Two probabilities, the probability to make a selection and the probability of a correct selection, are controlled by these selection procedures. Comparisons between the proposed selection procedures and certain earlier existing procedures are also made. The results show the superiority of the proposed selection procedures in terms of the required sample size.     

Modelling Resource Allocation in a Decentralized Organization with an AI-Based,Goal-Directive Model*

Modelling the resource allocation decision process in a decentralized organization using mathematical programming decomposition approaches has proven intractable for all but the smallest of problems. In this paper three artificial intelligence (AI) techniques are integrated to model the resource allocation decision process, and the solution for a three-level decentralized organization is illustrated. The techniques are (1) the filtered beam search, which selects a list of potential projects at the subordinate level, (2) the world model, which describes the ordinate and superordinate's worlds and their decision-making processes, and (3) the blackboard model, which allows for global, but selective, storage of information. Benefits of the new approach include: several different mechanisms of managerial control may be modelled, the true information flow in an organization is more closely mirrored, and problems of a more realistic size are now viable. There are three primary ways in which the new model could be useful to management: The desirability and effects of different organizational structures can be modeled, the efficacy of various coordination mechanisms along the organizational structure can be examined, and a subset of projects from a wider list of possibilities can be selected. Also, an example is given showing how the model may be extended to scenarios with asymetric information and divergence of preferences, whereby subordinates have different objectives than their managers and where there is no way for managers to verify the truthfulness of their subordinates' responses.