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Cold chains play an important role in reducing food spoilage, attracting food safety sensitive consumers, and guaranteeing food safety. Despite these advantages, the implementation of cold chains also calls for massive investment. Considering both costs and benefits of cold chains, our research established an optimization model for a fresh food supply chain to maximize its members' profits. Optimal investment levels of cold chain construction and advertisement, along with optimal pricing, were determined. The analysis shows that collaborative cold chain investment and collaborative pricing are superior strategies for the supply chain. Furthermore, we discuss the role of consumer food safety awareness and observe relatively high levels of cold chain investments and the mutually reinforcing effect of supply chain members' cold chain investments in a food safety sensitive market. Therefore, we suggest that governments should encourage improved food safety awareness among consumers to motivate cold chain investment and thus guarantee food safety. [ABSTRACT FROM AUTHOR]

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Byline: Li Zhu, Lothar Schulze, Lindu Zhao In global supply chains, increasing global sourcing costs have urged multinational automotive manufacturing firms to develop competitive international sourcing strategies. Faced with different international sourcing strategies between Original Equipment Manufacturers (OEMs) and suppliers in the automotive industry, this paper focuses on the comparative study of two popular ones (Risk Sharing or RS and Early Commitment or EC) and then tries to find out which of these is a better strategy in different situations. Using the real-options approach, the valuation models of the RS and EC sourcing strategies are established. By means of the binomial lattice technique depicting the uncertain exchange rate factor, we present the numerical simulation and sensitivity analysis of two Stochastic Dynamic Programming (SDP) problems. The results of our comparison analysis suggest that the EC sourcing strategy is better than its RS counterpart, especially when the foreign exchange rate is highly volatile in the global automobile supply chain.

As a growing number of low-resolution (LR) face images are captured by surveillance cameras, LR face recognition has been a hot issue for recent years. Previous efforts on LR face recognition typically assume each subject has multiple high-resolution (HR) training samples. However, this assumption may not hold in some special cases such as law-enforcement where only a single HR sample per person exists in the training set. For LR face recognition in SSPP scenario, it often suffers from overfitting and singular matrix problems. In this paper, we are the first to investigate LR face recognition with single sample per person, and propose a cluster-based regularized simultaneous discriminant analysis (C-RSDA) method based on SDA. C-RSDA regularizes the between-class and within-class scatter matrices respectively with inter-cluster and intra-cluster scatter matrices, where the cluster-based scatter matrices are computed from unsupervised clustering. With the cluster-based scatter matrices, not only the singularity problem is resolved, but overfitting problem is overcomed as more variations are exploited from the limited training samples. Thus, the proposed C-RSDA enhances the discriminative power of the feature subspace. We extensively evaluate C-RSDA on recognizing LR face images captured in both controlled and uncontrolled environments. The encouraging experimental results demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper examines contingent rerouting strategy for enhancing supply chain resilience taking a supplier's point of view. We consider a supply chain with multiple suppliers at each stage and establish a mathematical model for product allocation behavior among different suppliers. The allocation model is based on each supplier's production capacity, product quality, production cost, as well as possible decision maker's preferences. As a performance measure for rerouting strategy, we use the total outflow of the supply chain. We propose an optimization model and its solution determines the rerouting strategy for product flow through the supply chain under disruptions. Numerical examples demonstrate the effect of the rerouting strategy and show the resilience of the supply chain. [ABSTRACT FROM AUTHOR]