Compression of Deep Neural Networks on the Fly

Thanks to their state-of-the-art performance, deep neural networks are increasingly used for object recognition. To achieve these results, they use millions of parameters to be trained. However, when targeting embedded applications the size of these models becomes problematic. As a consequence, their usage on smartphones or other resource limited devices is prohibited. In this paper we introduce a novel compression method for deep neural networks that is performed during the learning phase. It consists in adding an extra regularization term to the cost function of fully-connected layers. We combine this method with Product Quantization (PQ) of the trained weights for higher savings in storage consumption. We evaluate our method on two data sets (MNIST and CIFAR10), on which we achieve significantly larger compression rates than state-of-the-art methods

The Multi-Location Transshipment Problem with Positive Replenishment Lead Times

Transshipments, monitored movements of material at the same echelon of a supply chain, represent an effective pooling mechanism. With a single exception, research on transshipments overlooks replenishment lead times. The only approach for two-location inventory systems with non-negligible lead times could not be generalized to a multi-location setting, and the proposed heuristic method cannot guarantee to provide optimal solutions. This paper uses simulation optimization by combining an LP/network flow formulation with infinitesimal perturbation analysis to examine the multi-location transshipment problem with positive replenishment lead times, and demonstrates the computation of the optimal base stock quantities through sample path optimization. From a methodological perspective, this paper deploys an elegant duality-based gradient computation method to improve computational efficiency. In test problems, our algorithm was also able to achieve better objective values than an existing algorithm.Transshipment;Infinitesimal Perturbation Analysis (IPA);Simulation Optimization

Multiple multi-tier sustainable supply chain management: a social systems theory perspective

A multi-tier supply chain is a complex system as it covers a focal company and multiple tiers of suppliers in a complex supply chain network. This study explores the complexity in multi-tier sustainable supply chain management (SSCM) through a social systems theory perspective. We carried out a case study on IKEA China’s sustainable cotton initiative and examined its five cotton-textile supply chains. The primary data were collected through 22 semi-structured interviews with managers of IKEA China and their multi-tier suppliers. The findings suggest that in order to cope with environmental complexity in implementing multi-tier sustainable initiatives, focal companies tend to create both internal complexity and collaborative complexity in a variety of governance mechanisms. In addition, environmental overlap and available collaborative complexity increase in this process and can feed back into systems to facilitate further creation of requisite variety. We contribute to the multi-tier SSCM literature through providing an in-depth understanding of nuanced mechanisms of managing different tiers of suppliers to cope with complexities by adopting a social systems theory perspective. We also contribute to multi-tier supply chain governance mechanisms from an evolution perspective

IKEA: global sourcing and the sustainable leather initiative

The leather industry has traditionally been characterized by global operations across both developed and developing countries. Due to the long distance and contextual differences, there are numerous sustainability issues occurring along the global leather supply chain. Addressing these issues is both a responsibility and a challenge for multinational companies, especially in their global sourcing (GS) activities. This teaching case provides an example of implementing the sustainable leather initiative in the global sourcing process at IKEA. The case demonstrates IKEA’s sustainable leather initiative supported by its tailored GS strategy and GS structure and provides a benchmark of Sustainable GS for multinational companies and allows for a thorough discussion of how to implement a sustainability initiative while conducting GS. The case can be used to teach graduate/postgraduate in agricultural business, MBA and executive students on sustainable supply chain management and corporate social responsibility