Single process plan scheduling with genetic algorithms

AIn this paper, a genetic algorithm model for scheduling manufacturing resources is developed for the case when there is only one process plan available per job, hence there is no routeing flexibility. The scheduling objectives considered are minimizing the makespan and mean flow time. Genetic algorithms design issues are discussed and the working of the employed genetic operators is explained in detail. Parameters for the genetic algorithms used for single process plan scheduling SPPS problems are set through extensive experimentation. Finally, the genetic algorithms approach is compared with several other approaches in terms of optimality of solution and computAuthors: ing time. It was observed that in most cases the genetic algorithms approach performed better than other approaches both in terms of finding an optimal or near optimal solution as well as computing time.     

University-to-industry knowledge transfer: literature review and unanswered questions

This paper reviews the economic literature concerning university-to-industry knowledge transfer. Papers on this topic are divided into four categories. Research in the 'firm characteristics' category focuses directly on company issues, such as internal organization, resource allocation, and partnerships. In contrast, research in the 'university characteristics' stream pays little attention to the firms that commercialize inventions, but rather focuses on issues relating to the university, such as licensing strategies, incentives for professors to patent, and policies such as taking equity in return for intellectual property. The 'geography in terms of localized spillovers' stream of research considers the spatial relationship between firms and universities relative to performance in terms of knowledge transfer success. Finally, the 'channels of knowledge transfer' literature examines the relative importance of various transfer pathways between universities and firms, such as publications, patents, and consulting. Each of these research streams is discussed and key papers are described highlighting important methodologies and results. Finally, an outline of topics requiring further research in each of the four categories is offered.     

‘You have to choose your childcare to fit your work’: Childcare decision-making among low-income working families

Regardless of their economic background, most working parents face the task of arranging childcare at some point. The decision-making process they experience is often complex, and this complexity is intensified for particular groups of families with limited financial and social resources. In this paper, we present findings from a three-year qualitative study of the childcare choices of low-income working families, many of whom were immigrants, had limited English proficiency, were parents of children with special needs, or represented some combination of these factors. The study explored families' current care arrangements, their reasons for selecting a particular form of childcare, and the characteristics of their ideal arrangements. Data were coded to identify themes in parental preferences, decision factors, and the barriers families faced in accessing their preferred care arrangements. Most significantly, the parents studied described their preferences for an environment where their children could learn and be in the presence of caring and trustworthy caregivers. About a third of the families said they preferred relatives as caregivers, and selected relatives to provide childcare. Other parents selected care according to cost, location, and availability of the provider; they described the challenges of locating affordable, high-quality care that met their nonstandard schedules. These findings have important implications for childcare policy.     

Comparison of Nonparametric and Parametric Methods in Repeated Measures Designs - A Simulation Study

This study investigates the performance of parametric and nonparametric tests to analyze repeated measures designs. Both multivariate normal and exponential distributions were simulated for varying values of the correlation and ten or twenty subjects within each cell. For multivariate normal distributions, the type I error rates were lower than the usual 0.05 level for nonparametric tests, whereas the parametric tests without the Greenhouse-Geisser or the Huynh-Feldt adjustment produced slightly higher type I error rates. Type I error rates for nonparametric tests, for multivariate exponential distributions, were more stable than parametric, Greenhouse-Geisser or Huynh-Feldt adjusted tests. For ten subjects within each cell, the parametric tests were more powerful than nonparametric tests. For twenty subjects per cell, the power of the nonparametric and parametric tests was comparable.     

Stochastic boosting algorithms

In this article we develop a class of stochastic boosting (SB) algorithms, which build upon the work of Holmes and Pintore (Bayesian Stat. 8, Oxford University Press, Oxford, 2007). They introduce boosting algorithms which correspond to standard boosting (e.g. Bühlmann and Hothorn, Stat. Sci. 22:477–505, 2007) except that the optimization algorithms are randomized; this idea is placed within a Bayesian framework. We show that the inferential procedure in Holmes and Pintore (Bayesian Stat. 8, Oxford University Press, Oxford, 2007) is incorrect and further develop interpretational, computational and theoretical results which allow one to assess SB’s potential for classification and regression problems. To use SB, sequential Monte Carlo (SMC) methods are applied. As a result, it is found that SB can provide better predictions for classification problems than the corresponding boosting algorithm. A theoretical result is also given, which shows that the predictions of SB are not significantly worse than boosting, when the latter provides the best prediction. We also investigate the method on a real case study from machine learning.     

An Empirical Investigation of the Contribution of Strategic Sourcing to Manufacturing Flexibilities and Performance*

Empirical studies for achieving manufacturing flexibility goals have centered around the uses and advantages of advanced technology. Few studies have examined alternative ways of attaining flexibility objectives. Strategic sourcing finds mention in the literature as a potential route to manufacturing flexibility. However, little empirical evidence exists to validate this view. Literature also describes manufacturing flexibility as a multidimensional concept but fails to adequately examine the synergies among the different dimensions. This research investigates the influence of strategic sourcing and advanced manufacturing technologies on specific manufacturing flexibilities, and examines relationships among different flexibilities. The results are tied to manufacturing cost reduction. The findings suggest that strategic sourcing can assist in the achievement of modification flexibilities. Volume and modification flexibility are found to influence new product flexibility. Modification flexibility is found to influence manufacturing cost reduction. The results show that strategic sourcing can be used to target specific manufacturing flexibilities and that interflexibility synergies need to be considered while formulating flexibility-based manufacturing strategies.     

Confidence in Domestic Money and Currency Substitution

This article studies currency substitution in a model where domestic money suffers from lack of confidence. When agents' confidence is exogenous and constant, there is a unique but unstable dual-money steady state. However, when agents' confidence is updated endogenously, the dynamics of currency substitution are driven by agents' evolving beliefs, and the economy always converges to an equilibrium where both monies circulate. Therefore, the economy under endogenous beliefs exhibits both persistence in currency substitution and tenacity of domestic money. Furthermore, in general, there are multiple steady states, which can be Pareto ranked by the degree of currency substitution.     

On the adoption of lean manufacturing principles in process industries

Traditionally, the lean paradigm has been applied to discrete manufacturing of items that can be easily put together and taken apart. The process industry, on the other hand, transforms raw materials into cohesive units that are basically blended into a final product with parts that cannot be disassembled and then reassembled. The current lean literature provides numerous commendable examples of theory and practices of lean principles in discrete manufacturing. However, its application in process industry is limited. Furthermore, there is no systematic accounting of the lean literature in this sector, which may have contributed to lesser awareness in the industry. This paper provides a state-of-the-art review of lean manufacturing literature with respect to its applications in process industry. It contributes to the classification of literature in a manner which helps to identify strategies suitable for the adoption of lean concepts in process industry. The paper seeks to synthesise the literature with an emphasis on identifying the scope for lean in process industry and associated benefits. The review also presents an analysis of the lean tools and techniques that have been applied or have potential application in the process industry and the challenges to implement lean. We believe that such a comprehensive review will not only facilitate the adoption of lean in process industry but will also provide agenda for further research by exposing voids in the knowledge base.     

A Contingent View of Quality Management‐The Impact of International Competition on Quality

Much of the research on quality practices and performance reflects a resource‐based perspective of the firm, dealing primarily with internal issues of managerial and technological competence in developing and executing an effective TQM strategy. The neoclassical perspective on the influence of the competitive environment on quality practices and performance remains conspicuously absent in the empirical quality literature. Our study aims to address this gap by examining the contingent role of international competition on quality management and performance. We develop and test an integrative framework of quality management, consisting of high involvement work practices, quality practices, quality performance, and firm performance. We then examine the contingent effects of international competition on the constructs and relationships of the framework. International competition was found to moderate the relationship between quality practices and customer satisfaction performance, as well as the relationship between high involvement work practices and firm performance. The moderator effects suggest interesting implications for quality theory and practice.