An integrated method for airline company supplier selection based on the entropy and vikor methods: a real case study

All certified airlines require to implement a safety and quality management system. Therefore, the quality of all services and products with critical operational domains have been challenging issues in the aviation industry. In this regard, supplier selection plays an important role to acquire competitive benefits. Flight operations is critical scope in an airline and their outputs have a direct impact on flight safety consequences. Therefore, the quality of supplier’s product and services play the main role in their flight operations process. In this research, a new decision-making framework is developed to evaluate the performance of the suppliers based on the Entropy and VIKOR approaches. At the outset, the main criteria and sub-criteria are identified based on the literature and expert\u27s viewpoint and then their weights are calculated using the Entropy method. Afterward, the potential suppliers are ranked using the VIKOR method. The airline supplier’s assessment through expert judgment and integrated criteria are the new approaches that are developed in this paper. The obtained results show that economic, quality and safety, and reputation respectively are the main criteria to select suppliers

Generic modelling and simulation of operations and stock levels in supply chains

Imperial Users onl

Supply Chain Simulation: Experimentation without Pain

Bridging the gap between theory and practice has always been a key issue for students and graduates. The magnitude and scope of subject areas that students at third level institutions have to learn in theory means that visualising them without any practical experience can be very difficult. Understanding the complexity of supply chain networks and how to manage them create a considerable level of difficulty for students and professionals. Theories and applications included in supply chain management subjects are the key to empathise the real challenges. Nevertheless, teaching these theories needs substantial efforts and new innovative approaches to deliver the concepts and assure successful transfer of the learning outcomes. To complicate things more, the levels of uncertainty and risk within an entire supply chain are still not fully recognised or understood even by industry professionals. Research studies showed the need for more transparency and collaborative approaches to take place among supply chain partners in order to achieve more sustainable operations. Making sure students comprehend the scale of activities and stochastic nature of a supply chain before they carry on their industrial careers is therefore crucial. Using computer simulation integrated with structured modelling techniques, a detailed, animated and generic supply chain simulation-based learning framework can be developed to incorporate many areas of learning undertaken by students in relation to the supply chain management. Experimenting on the simulation models allow the students to examine quantitatively the impact of changing critical factors (e.g. inventory level, demand, suppliers’ lead time) on the performance of supply chain. This paper demonstrates the impact of using interactive simulation technologies in teaching third level education with special reference to supply chain management and discusses the benefits of learning through such a level of immersion

Web-Based Supply Chain Simulation: an Integrated Approach

This is an era marked by rapid technology development in all different educational arenas. Alongside this growing demand of technology, learning process is getting new forms and hence traditional teaching approaches tend to struggle and lack the requisite qualities to meet new generation expectations. In third level education, this problem is increasing in magnitude and new dimensions, especially when it comes to teaching difficult subjects such as supply chain management. Understanding the complexity of supply chain networks and how to manage them create a considerable level of difficulty for students and professionals. Collaboration between supply chain members is now recognised as an important strategic factor in creating a solution to the complexity of the supply chain system. New technologies are beginning to bring a huge transformation into teaching delivery methods. This paper presents an integrated web-based simulation framework that supports learning supply chain concepts and challenges. Simulation-based learning environment allow participants to examine various management strategies without real disruptions to the current system. Using supply chain simulation creates a vibrant experience and a better understanding to the impact of uncertainty and risks within supply chains. Integrating web technologies to simulation has added an edge to the learning environment with the friendly graphical user interface

Seismic history matching using proxy models

Generally, reservoir simulation is used to predict field performance and analyse uncertainties for assistance in decision making, while history matching is a key step in reservoir simulation, which is a process of model adjustment and simulation runs with different reservoir parameter settings until the differences between simulated data and historical data reach minima. An efficient reservoir simulation model must be the one that can predict reservoir performance and update history matching results continuously by modifying the reservoir model as long as new data become available. However, reservoir simulation can be very time consuming, depending on the complexity of the reservoir model, and history matching is even more computationally expensive, since it requires many simulation runs. Recently, intelligent technology advances in the oil and gas industry, have initiated a new era of big data. As different varieties of data have been integrated to make better decisions, together with the generation of high frequency data streams, a major concern for petroleum engineers is how reservoir simulation should be calibrated in line with the real time data without compromising the simulation time. In the seismic history matching (SHM) workflow this may be a more obvious issue than in the conventional well production history matching. In order to address this problem, many studies have been undertaken. Besides increasing computational power, various types of research have focused on speeding up the reservoir simulation process, especially history matching, by either implementing optimisation algorithms or generating efficient proxy models. Nevertheless, there has not yet been a standard method recognized in reservoir simulation. In this study, a novel method has been proposed as an attempt to investigate the possibility of achieving efficient seismic history matching by data-driven proxy models. This thesis essentially involves detailing background motivations, proxy model building, followed by its testing and application in SHM. Comparisons of proxy models with conventional simulators have been made from different aspects. The objective is mainly focused on examining the capability of the proxy models as a simplification of the conventional physics-based simulators in SHM. According to the simulation results, the feasibility of the combination of proxy models has been proven to be successful and efficient. Importantly, huge amounts of time and effort have been saved in the reservoir simulation process. In addition, it is suggested that other challenges of SHM, such as multi-domain comparison and multi-field communication, could be tackled by using the proxy method

From FPGA to ASIC: A RISC-V processor experience

This work document a correct design flow using these tools in the Lagarto RISC- V Processor and the RTL design considerations that must be taken into account, to move from a design for FPGA to design for ASIC

Generalising history matching for enhanced calibration of computer models

History matching using Gaussian process emulators is a well-known methodology for the calibration of computer models. It attempts to identify the parts of input parameter space that are likely to result in mismatches between simulator outputs and physical observations by using emulators. These parts are then ruled out. The remaining “Not Ruled Out Yet (NROY)” input space is then searched for good matches by repeating the history matching process. The first section of this thesis illustrates an easily neglected limitation of standard history matching: the emulator must simulate the target NROY space well, else good parameter choices can be ruled out. We show that even when an emulator passes standard diagnostic checks on the whole parameter space, good parameter choices can easily be ruled out. We present novel methods for detecting these cases and a Local Voronoi Tessellation method for a robust approach to calibration that ensures that the true NROY space is retained and parameter inference is not biased. The remainder of this thesis looks into developing a generalised history matching for calibrating computer models with high-dimensional output. We address another limitation of the standard (PCA-based) history matching, which only works well when the parameters are responsible for the strength of various patterns. We show that when the parameters control the position of patterns, e.g. shifting currents, current approaches will not generally be able to calibrate these models. To overcome this, we extend history matching to kernel feature space, where output space for moving patterns can be compared with the observations. We develop kernel-based history matching as a generalisation to history matching and examine the multiple possible interpretations of the usual implausibility measure and threshold for defining NROY. Automatic kernel selection based on expert modeller judgement is introduced to enable the experts to define important features that the model should be able to reproduce

Simulation in Supply Chains: An Arena basis

<p>ENGLISH ABSTRACT: The quest for global competitiveness brought about new business approaches, of which the supply chain has become an important entity during the last few years. With even more complex decision structures, demand variation and the need for evaluating alternatives within this frame, simulation and simulation-optimization have been identified as key decision-making tools. This paper briefly reviews the basic characteristics of supply chains, and illustrates that existing software may be integrated towards a supply chain simulator.</p><p>AFRIKAANSE OPSOMMING: Die strewe na globale mededingendheid vereis nuwe benaderings deur ondernemings, terwyl die toevoerketting 'n belangrike entiteit gedurende die afgelope paar jaar geword het. Toenemende kompleksiteit in besluitneming, variasie in vraag en die behoefte om alternatiewe binne hierdie komplekse raamwerk te evalueer, het tot gevolg dat simulasie en simulasie-optimering as sleutel-besluitneming gereedskap beskou word. Hierdie artikel gee 'n kort oorsig oor die basiese eienskappe van toevoerkettings, en dit word getoon dat bestaandeprogrammatuur integreer kan word om 'n toevoerketting-simuleerderte ontwikkel.</p&gt