A framework for designing robust food supply chains

After years of emphasis on leanness and responsiveness businesses are now experiencing their vulnerability to supply chain disturbances. Although more literature is appearing on this subject, there is a need for an integrated framework to support the analysis and design of robust food supply chains. In this chapter we present such a framework. We define the concept of robustness and classify supply chain disturbances, sources of food supply chain vulnerability, and adequate redesign principles and strategies to achieve robust supply chain performances. To test and illustrate its applicability, the research framework is applied to a meat supply chain.

Adaptive linear combination of heuristic orderings in constructing examination timetables

In this paper, we investigate adaptive linear combinations of graph coloring heuristics with a heuristic modifier to address the examination timetabling problem. We invoke a normalisation strategy for each parameter in order to generalise the specific problem data. Two graph coloring heuristics were used in this study (largest degree and saturation degree). A score for the difficulty of assigning each examination was obtained from an adaptive linear combination of these two heuristics and examinations in the list were ordered based on this value. The examinations with the score value representing the higher difficulty were chosen for scheduling based on two strategies. We tested for single and multiple heuristics with and without a heuristic modifier with different combinations of weight values for each parameter on the Toronto and ITC2007 benchmark data sets. We observed that the combination of multiple heuristics with a heuristic modifier offers an effective way to obtain good solution quality. Experimental results demonstrate that our approach delivers promising results. We conclude that this adaptive linear combination of heuristics is a highly effective method and simple to implement.

Bricks vs. clicks: Which is better for marketing remanufactured products?

The economical and environmental benefits are the central issues for remanufacturing. Whereas extant remanufacturing research focuses primarily on such issues in remanufacturing technologies, production planning, inventory control and competitive strategies, we provide an alternative yet somewhat complementary approach to consider both issues related to different channels structures for marketing remanufactured products. Specifically, based on observations from current practice, we consider a manufacturer sells new units through an independent retailer but with two options for marketing remanufactured products: (1) marketing through its own e-channel (Model M) or (2) subcontracting the marketing activity to a third party (Model 3P). A central result we obtain is that although Model M is always greener than Model 3P, firms have less incentive to adopt it because both the manufacturer and retailer may be worse off when the manufacturer sells remanufactured products through its own e-channel rather than subcontracting to a third party. Extending both models to cases in which the manufacturer interacts with multiple retailers further reveals that the more retailers in the market, the greener Model M relative to Model 3P.

Using the hidden Markov model to capture quality of care in Lombardy geriatric wards

Quality of care is an important aspect of healthcare monitoring, which is used to ensure that the healthcare system is delivering care of the highest standard. With populations growing older there is an increased urgency in making sure that the healthcare delivered is of the highest standard. Healthcare providers are under increased pressure to ensure that this is the case with public and government demand expecting a healthcare system of the highest quality. Modelling quality of care is difficult to measure due to the many ways of defining it. This paper introduces a potential model which could be used to take quality of care into account when modelling length of stay. The Coxian phase-type distribution is used to model length of stay and the associated quality of care incorporated into the Coxian using a Hidden Markov model. Covariates are also introduced to determine their impact on the hidden level to find out what potentially can affect quality of care. This model is applied to geriatic patient data from the Lombardy region of Italy. The results obtained highlighted that bed numbers and the type of hospital (public or private) can have an effect on the quality of care delivered.

A constructive approach for examination timetabling based on adaptive decomposition and ordering

In this study, we investigate an adaptive decomposition and ordering strategy that automatically divides examinations into difficult and easy sets for constructing an examination timetable. The examinations in the difficult set are considered to be hard to place and hence are listed before the ones in the easy set in the construction process. Moreover, the examinations within each set are ordered using different strategies based on graph colouring heuristics. Initially, the examinations are placed into the easy set. During the construction process, examinations that cannot be scheduled are identified as the ones causing infeasibility and are moved forward in the difficult set to ensure earlier assignment in subsequent attempts. On the other hand, the examinations that can be scheduled remain in the easy set.

Within the easy set, a new subset called the boundary set is introduced to accommodate shuffling strategies to change the given ordering of examinations. The proposed approach, which incorporates different ordering and shuffling strategies, is explored on the Carter benchmark problems. The empirical results show that the performance of our algorithm is broadly comparable to existing constructive approaches.

A TMA De-Arraying Method for High Throughput Biomarker Discovery in Tissue Research

Background: Tissue MicroArrays (TMAs) represent a potential high-throughput platform for the analysis and discovery of tissue biomarkers. As TMA slides are produced manually and subject to processing and sectioning artefacts, the layout of TMA cores on the final slide and subsequent digital scan (TMA digital slide) is often disturbed making it difficult to associate cores with their original position in the planned TMA map. Additionally, the individual cores can be greatly altered and contain numerous irregularities such as missing cores, grid rotation and stretching. These factors demand the development of a robust method for de-arraying TMAs which identifies each TMA core, and assigns them to their appropriate coordinates on the constructed TMA slide.

Methodology: This study presents a robust TMA de-arraying method consisting of three functional phases: TMA core segmentation, gridding and mapping. The segmentation of TMA cores uses a set of morphological operations to identify each TMA core. Gridding then utilises a Delaunay Triangulation based method to find the row and column indices of each TMA core. Finally, mapping correlates each TMA core from a high resolution TMA whole slide image with its name within a TMAMap.

Conclusion: This study describes a genuine robust TMA de-arraying algorithm for the rapid identification of TMA cores from digital slides. The result of this de-arraying algorithm allows the easy partition of each TMA core for further processing. Based on a test group of 19 TMA slides (3129 cores), 99.84% of cores were segmented successfully, 99.81% of cores were gridded correctly and 99.96% of cores were mapped with their correct names via TMAMaps. The gridding of TMA cores were also extensively tested using a set of 113 pseudo slide (13,536 cores) with a variety of irregular grid layouts including missing cores, rotation and stretching. 100% of the cores were gridded correctly.

Defining a Research Agenda in Value Driven Design: Questions That Need to be Asked

Value driven design is an innovative design process that utilizes the optimization of a system level value function to determine the best possible design. This contrasts with more traditional systems engineering techniques, which rely on satisfying requirements to determine the design solution. While ‘design for value’ is intuitively acceptable, the transformation of value driven design concepts into practical tools and methods for its application is challenging. This, coupled with the growing popularity of value-centric design philosophies, has led to a proposed research agenda in value driven design. This research agenda asks fundamental questions about the design philosophy and attempts to identify areas of significant challenge. The research agenda is meant to stimulate discussion in the field, as well as prompt research that will lead to the development of tools and methodologies that will facilitate the application of value driven design and further the state of the art.

Implementation Experiences from Smart Grid Security Applications and Outlook on Future Research

Experiences from smart grid cyber-security incidents in the past decade have raised questions on the applicability and effectiveness of security measures and protection mechanisms applied to the grid. In this chapter we focus on the security measures applied under real circumstances in today’s smart grid systems. Beginning from real world example implementations, we first review cyber-security facts that affected the electrical grid, from US blackout incidents, to the Dragonfly cyber-espionage campaign currently focusing on US and European energy firms. Provided a real world setting, we give information related to energy management of a smart grid looking also in the optimization techniques that power control engineers perform into the grid components. We examine the application of various security tools in smart grid systems, such as intrusion detection systems, smart meter authentication and key management using Physical Unclonable Functions, security analytics and resilient control algorithms. Furthermore we present evaluation use cases of security tools applied on smart grid infrastructure test-beds that could be proved important prior to their application in the real grid, describing a smart grid intrusion detection system application and security analytics results. Anticipated experimental results from the use-cases and conclusions about the successful transitions of security measures to real world smart grid operations will be presented at the end of this chapter.

Environmental Operations Management and its links with Proactivity and Performance: A study of the UK Food Industry

Two important strands of research within the literature on Environmental Operations Management (EOM) relate to environmental approach and performance. Often in this research the links between environmental approach, environmental performance and EOM are considered separately with little consideration given to the interrelationships between them. This study develops and tests a theoretical framework that combines these two strands to explore how UK food manufacturers approach EOM. The framework considers the relationships between an environmentally pro-active strategic orientation, EOM and environmental and cost performance. A cross-sectional survey was developed to collect data from a sample of 1200 food manufacturing firms located within the UK. Responses were sought from production and operations managers who are knowledgeable about the environmental operations practices within their firms. A total of 149 complete and useable responses were obtained. The reliability and validity of the scales used in the survey were tested using exploratory factor analysis, prior to the testing of the hypotheses underpinning the theoretical framework using hierarchical regression analysis. Our results generate support for a link between environmental proactivity, environmental practices and performance, consistent with the natural resource-based view (NRBV) and a number of studies in the extant literature. In considering environmental proactivity as a standalone concept that influences the implementation of environmental practices outlined in the NRBV, our study generates some novel insights into these links. Further our results provide some interesting insights for managers within the food industry who can identify the potential benefits of certain practices for performance within this unique context.

The impact of an integral student engagement approach on teaching Operations and Supply Chain Management

In this study we investigate the influence of the implementation of multidimensional engagement on students’ academic, social and emotional outcomes in the teaching of Operations and Supply Chain Management (OSCM) modules. Next to the academic and behavioural engagement dimensions, which are traditionally used to engage students in OSCM courses, we also incorporate a cognitive dimension to enhance integral student engagement. Up to know, integral student engagement is not reported in the OSCM literature. Cognitive engagement is based on implementation of summative self- and peer-assessment of weekly assignments. Our investigation is based on action research, conducted in an OSCM module over two consecutive years. We found that, in general, multidimensional engagement results in higher levels of academic performance, development of relationships with academic staff and their peers and emotional satisfaction. These findings are discussed in relation to several contextual factors: nature of the study material, gender, and the home location of students.