Modelling an End-to-End Supply Chain System Using Simulation

Supply chains (SCs) are an important part of today’s world. Many businesses operate in the global marketplace where individual companies are no longer treated as separate entities, but as a vital part of an end-to-end supply chain (E2E-SC) system. Key challenges and issues in managing E2E-SCs are duly attributed to their extended, complex and systemic nature. In the era of uncertainty, risks and market volatility, decision makers are searching for modelling techniques to be able to understand, to control, design or evaluate their E2E-SC. This research aims to support academics and decision makers by defining a generic simulation modelling approach that can be used for any E2E-SC. This study considers the challenges and issues associated with modelling complex E2E-SC systems using simulation and underlines the key requirements for modelling an E2E-SC. The systematic literature review approach is applied to provide a twofold theoretical contribution [a] an insightful review of various contributions to knowledge surrounding simulation methods within the literature on end-to-end supply chains and [b] to propose a conceptual framework that suggests generic elements required for modelling such systems using simulation. The research adopts a simulation methodology and develops a generic guide to an E2E-SC simulation model creation process. It is a mindful inquiry into the implications relative to a simulation model development process in presence of generic elements from the proposed conceptual framework. The conceptual framework is validated with industry experts and insightful remarks are drawn. In conclusion, it is acknowledged that modelling an E2E-SC system using simulation is a challenge, and this area is not fully exploited by the business. A guide to an E2E-SC simulation model development is a theoretical and practical contribution of this research, immensely sought by businesses, which are continuously tackling day to day issues and challenges, hence often lacking resources and time to focus on modelling. The conceptual framework captures generic elements of the E2E-SC system; however, it also highlights multiple challenges around simulation model development process such as technical constraints and almost impracticability of a true reflection of an E2E-SC system simulation model. The significant contribution of this thesis is the evaluation of the proposed generic guide to E2E-SC simulate model development, which provides the architecture for better strategic supply and demand balancing as new products, price fluctuations, and options for physical network changes can be dynamically incorporated into the model. The research provides an insightful journey through key challenges and issues when modelling E2E-SC systems and contributes with key recommendations for mindful inquiries into E2E-SC simulation models

Developing a conceptual model of marine farming in New Zealand

Survey and Geographic Information System (GIS) data analysis describes the relative influence of biophysical and human variables on site choices made by marine farmers in New Zealand. Community conflicts have grown in importance in determining farm location and different government planning strategies leave distinct signature patterns. Recent legislation empowers local governments to choose among three strategies for future regional aquaculture development. This paper suggests each strategy could result in different spatial outcomes. Simulation modelling of the type described here can provide a better understanding of farmer responses to management approaches and the range of futures that could result from planning choices made today

Enhancing Energy Production with Exascale HPC Methods

High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the Intel Corporation, which enabled us to obtain the presented experimental results in uncertainty quantification in seismic imagingPostprint (author's final draft