scholarly journals Introducing systemic risk management to engineering consultation industry: A case study

2019 ◽  
Vol 281 ◽  
pp. 04002
Author(s):  
Reem S. AbdAlla ◽  
Fouad Khalaf
Keyword(s):  
Risk Management ◽  
Systemic Risk ◽  
Real Life ◽  
Pilot Project ◽  
Hazard Identification ◽  
Industrial Project ◽  
Project Outcomes ◽  
Proposed Model ◽  
Engineering Consultation ◽  
Project Risks

Engineering consultation industry plays a central role in developing countries. This industry approaches risk management by using a set of practices related to risk which the industrial project are exposed. However, this limited angle does not satisfy the complexity and nature of real life risks. This paper introduces a systemic approach, supposedly to improve handling project risks through better identifying and managing project risks in the engineering consultancy in Egypt. The proposed model supports the holistic concepts of system definition and hazard identification. The model has been applied in one of Egyptian expert houses as a pilot project. Outcomes of this research will allow the engineering consultants to develop/improve performance if the proposed concepts of systemic risk management are applied.

Risk-Based Robust Bidding Strategies for EVs’ Aggregators in Day-ahead Markets with Uncertainty

2020 ◽  
Author(s):  
Ahmed Abdelmoaty ◽  
Wessam Mesbah ◽  
Mohammad A. M. Abdel-Aal ◽  
Ali T. Alawami
Keyword(s):  
Robust Optimization ◽  
Electricity Market ◽  
Real Life ◽  
Optimization Approach ◽  
Case Scenario ◽  
Worst Case ◽  
Bidding Strategies ◽  
Wind Generators ◽  
Proposed Model ◽  
Optimal Bidding

In the recent electricity market framework, the profit of the generation companies depends on the decision of the operator on the schedule of its units, the energy price, and the optimal bidding strategies. Due to the expanded integration of uncertain renewable generators which is highly intermittent such as wind plants, the coordination with other facilities to mitigate the risks of imbalances is mandatory. Accordingly, coordination of wind generators with the evolutionary Electric Vehicles (EVs) is expected to boost the performance of the grid. In this paper, we propose a robust optimization approach for the coordination between the wind-thermal generators and the EVs in a virtual<br>power plant (VPP) environment. The objective of maximizing the profit of the VPP Operator (VPPO) is studied. The optimal bidding strategy of the VPPO in the day-ahead market under uncertainties of wind power, energy<br>prices, imbalance prices, and demand is obtained for the worst case scenario. A case study is conducted to assess the e?effectiveness of the proposed model in terms of the VPPO's profit. A comparison between the proposed model and the scenario-based optimization was introduced. Our results confirmed that, although the conservative behavior of the worst-case robust optimization model, it helps the decision maker from the fluctuations of the uncertain parameters involved in the production and bidding processes. In addition, robust optimization is a more tractable problem and does not suffer from<br>the high computation burden associated with scenario-based stochastic programming. This makes it more practical for real-life scenarios.<br>

An Order Fulfillment Model for the LED Chip Manufacturing Plant

2013 ◽  
Vol 694-697 ◽  
pp. 3446-3452 ◽  
Author(s):  
Horng Huei Wu ◽  
Ming Feng Li ◽  
Tzu Fang Hsu
Keyword(s):  
Inventory Control ◽  
Real Life ◽  
Production Model ◽  
Order Fulfillment ◽  
Due Date ◽  
Make To Order ◽  
Proposed Model ◽  
General Production ◽  
Production Strategy ◽  
Production Output

The LED chip manufacturing (LED-CM) is an important process in the LED supply chain. The make-to-order production strategy is a general production model for the LED-CM plants to satisfy the variety requirement of their customers. However, the special features of the unstable production output and a product composed of the chips of different feasible Bins exist in the LED-CM plant. The production planner will confront the issue of effective inventory control and exact due-date performance under the severely competitive pressure. Therefore an effective order fulfillment procedure for production planners is a required key issue to accomplish the inventory control and exact due-date performance. An order fulfillment model for production planner is thus proposed in this paper to meet the requirement of the LED-CM plants. A real-life LED-CM case is also utilized to demonstrate and evaluate the application and effectiveness of the proposed model.

Management of Fiscal and Financial Risks Generated by PPPs: Conceptual Issues and Country Experiences

2018 ◽  
Author(s):  
Edgardo C. Demaestri ◽  
Cynthia Moskovits ◽  
Jimena Chiara
Keyword(s):  
Risk Management ◽  
Latin American ◽  
Institutional Capacity ◽  
Debt Management ◽  
Financial Risks ◽  
Successful Development ◽  
Contingent Liabilities ◽  
Project Risks ◽  
The Caribbean ◽  
Risks Assessment

This paper discusses the main issues concerning sovereign fiscal and financial risks from public–private partnerships (PPPs) with a focus on contingent liabilities (CLs). It is based on the presentations and discussions that took place during the XI Annual Meeting of the Group of Latin American and the Caribbean Debt Management Specialists (LAC Debt Group), held in Barbados in August 2015. The main issues discussed include PPP risks assessment, institutional framework for PPP risk management, and accounting and reporting of CLs generated by PPPs. Six country cases (Chile, Colombia, Costa Rica, Honduras, Suriname, and Turkey) are presented to illustrate experiences with different degrees of development regarding the management of risks and CLs related to PPPs. The document concludes that PPP risk management should encompass the whole lifecycle of a PPP project, risks need to be identified and CLs must be estimated and monitored, and the institutional capacity of governments to evaluate and manage PPP risks plays a central role in the successful development of PPP contracts. Although institutional capacities in this regard have improved in recent years, estimations of CLs involved in PPPs are not regularly performed, and there is still room for improvement on the assessment, measurement, registration, budgeting, and reporting of risks and CLs related to PPPs.

A robust possibilistic programming model for production-routing problem in a three-echelon supply chain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Ali Beheshtinia ◽  
Narjes Salmabadi ◽  
Somaye Rahimi
Keyword(s):  
Supply Chain ◽  
Real Life ◽  
Model Parameters ◽  
Pickup And Delivery ◽  
Distribution Centers ◽  
Routing Problem ◽  
Remarkable Feature ◽  
Content Type ◽  
Proposed Model ◽  
Production Routing

Purpose This paper aims to provide an integrated production-routing model in a three-echelon supply chain containing a two-layer transportation system to minimize the total costs of production, transportation, inventory holding and expired drugs treatment. In the proposed problem, some specifications such as multisite manufacturing, simultaneous pickup and delivery and uncertainty in parameters are considered. Design/methodology/approach At first, a mathematical model has been proposed for the problem. Then, one possibilistic model and one robust possibilistic model equivalent to the initial model are provided regarding the uncertain nature of the model parameters and the inaccessibility of their probability function. Finally, the performance of the proposed model is evaluated using the real data collected from a pharmaceutical production center in Iran. The results reveal the proper performance of the proposed models. Findings The results obtained from applying the proposed model to a real-life production center indicated that the number of expired drugs has decreased because of using this model, also the costs of the system were reduced owing to integrating simultaneous drug pickup and delivery operations. Moreover, regarding the results of simulations, the robust possibilistic model had the best performance among the proposed models. Originality/value This research considers a two-layer vehicle routing in a production-routing problem with inventory planning. Moreover, multisite manufacturing, simultaneous pickup of the expired drugs and delivery of the drugs to the distribution centers are considered. Providing a robust possibilistic model for tackling the uncertainty in demand, costs, production capacity and drug expiration costs is considered as another remarkable feature of the proposed model.

Fuzzy preference programming formulation in data envelopment analysis for university department evaluation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dyanne Brendalyn Mirasol-Cavero ◽  
Lanndon Ocampo
Keyword(s):  
Data Envelopment Analysis ◽  
Real Life ◽  
The Philippines ◽  
Data Envelopment ◽  
Data Accessibility ◽  
Content Type ◽  
Proposed Model ◽  
University Department ◽  
Fuzzy Dea ◽  
Fuzzy Preference

Purpose University department efficiency evaluation is a performance assessment on how departments use their resources to attain their goals. The most widely used tool in measuring the efficiency of academic departments in data envelopment analysis (DEA) deals with crisp data, which may be, often, imprecise, vague, missing or predicted. Current literature offers various approaches to addressing these uncertainties by introducing fuzzy set theory within the basic DEA framework. However, current fuzzy DEA approaches fail to handle missing data, particularly in output values, which are prevalent in real-life evaluation. Thus, this study aims to augment these limitations by offering a fuzzy DEA variation. Design/methodology/approach This paper proposes a more flexible approach by introducing the fuzzy preference programming – DEA (FPP-DEA), where the outputs are expressed as fuzzy numbers and the inputs are conveyed in their actual crisp values. A case study in one of the top higher education institutions in the Philippines was conducted to elucidate the proposed FPP-DEA with fuzzy outputs. Findings Due to its high discriminating power, the proposed model is more constricted in reporting the efficiency scores such that there are lesser reported efficient departments. Although the proposed model can still calculate efficiency no matter how much missing and unavailable, and uncertain data, more comprehensive data accessibility would return an accurate and precise efficiency score. Originality/value This study offers a fuzzy DEA formulation via FPP, which can handle missing, unavailable and imprecise data for output values.

scholarly journals Modelling of Bi-Directional Spatio-Temporal Dependence and Users’ Dynamic Preferences for Missing POI Check-In Identification

2019 ◽  
Vol 33 ◽  
pp. 5458-5465 ◽  
Author(s):  
Dongbo Xi ◽  
Fuzhen Zhuang ◽  
Yanchi Liu ◽  
Jingjing Gu ◽  
Hui Xiong ◽  
...  
Keyword(s):  
Large Scale ◽  
Real Life ◽  
Location Prediction ◽  
Temporal Dependence ◽  
Great Opportunity ◽  
Mobility Data ◽  
Proposed Model ◽  
Poi Recommendation ◽  
Spatio Temporal ◽  
Dynamic Preferences

Human mobility data accumulated from Point-of-Interest (POI) check-ins provides great opportunity for user behavior understanding. However, data quality issues (e.g., geolocation information missing, unreal check-ins, data sparsity) in real-life mobility data limit the effectiveness of existing POIoriented studies, e.g., POI recommendation and location prediction, when applied to real applications. To this end, in this paper, we develop a model, named Bi-STDDP, which can integrate bi-directional spatio-temporal dependence and users’ dynamic preferences, to identify the missing POI check-in where a user has visited at a specific time. Specifically, we first utilize bi-directional global spatial and local temporal information of POIs to capture the complex dependence relationships. Then, target temporal pattern in combination with user and POI information are fed into a multi-layer network to capture users’ dynamic preferences. Moreover, the dynamic preferences are transformed into the same space as the dependence relationships to form the final model. Finally, the proposed model is evaluated on three large-scale real-world datasets and the results demonstrate significant improvements of our model compared with state-of-the-art methods. Also, it is worth noting that the proposed model can be naturally extended to address POI recommendation and location prediction tasks with competitive performances.

scholarly journals A Study on the Power Consumption of H.264/AVC-Based Video Sensor Network

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Bambang A. B. Sarif ◽  
Mahsa Pourazad ◽  
Panos Nasiopoulos ◽  
Victor C. M. Leung
Keyword(s):  
Power Consumption ◽  
Estimation Error ◽  
Real Life ◽  
Video Encoding ◽  
Energy Resources ◽  
Transmission Power ◽  
Proposed Model ◽  
Video Sensor Networks ◽  
Video Sensor ◽  
Important Design

There is an increasing interest in using video sensor networks (VSNs) as an alternative to existing video monitoring/surveillance applications. Due to the limited amount of energy resources available in VSNs, power consumption efficiency is one of the most important design challenges in VSNs. Video encoding contributes to a significant portion of the overall power consumption at the VSN nodes. In this regard, the encoding parameter settings used at each node determine the coding complexity and bitrate of the video. This, in turn, determines the encoding and transmission power consumption of the node and the VSN overall. Therefore, in order to calculate the nodes’ power consumption, we need to be able to estimate the coding complexity and bitrate of the video. In this paper, we modeled the coding complexity and bitrate of the H.264/AVC encoder, based on the encoding parameter settings used. We also propose a method to reduce the model estimation error for videos whose content changes within a specified period of time. We have conducted our experiments using a large video dataset captured from real-life applications in the analysis. Using the proposed model, we show how to estimate the VSN power consumption for a given topology.

scholarly journals THE CURRENT STATE OF PROJECT RISK ASSESSMENT AND EDUCATION NEEDS IN PROJECT RISK MANAGEMENT

2019 ◽  
Vol 7 ◽  
Author(s):  
Matej Masár ◽  
Mária Hudáková
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Project Managers ◽  
Project Risk Management ◽  
Project Risk ◽  
Qualitative And Quantitative ◽  
Current State ◽  
The World ◽  
Project Risks ◽  
Project Risk Assessment

Current trends show that education in the field of project risk management is a very actual topic. Long - term projects, which was realized in 2018, was mainly focused on R&D across the world. Short - term projects, was focused on innovation and improve manufacturing processes. Many projects failed because project managers did not manage project risks. Project managers have less knowledge and skills on how to effectively manage project risks, especially risks in the planning phase of projects. The main aim of this article is to analyze the current state of usage project risk assessment across the world, based on own empirical research, which was provided, by authors in 2018 and 2019 (mainly level of usage project risk management methods, experience and level of education). The research focused on analyzing the current state of project risk assessment among continents. The authors focused on the average level of use qualitative and quantitative project risk analysis by project managers, level of project risk management experience by project managers and complexity of learning in using of qualitative and quantitative project risk management methods and tools.  Some recommendation were established to educate project managers in the field of project risk management.

scholarly journals An Integrated Fuzzy Model for Selecting Resilient Suppliers in Electronics Industry of Iran

Logistics ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 71
Author(s):  
Hamzeh Aghababayi ◽  
Mohsen Shafiei Shafiei Nikabadi
Keyword(s):  
Real Life ◽  
Fuzzy Model ◽  
Electronics Industry ◽  
Electronic Industry ◽  
Chain Management ◽  
Fuzzy Environment ◽  
Proposed Model ◽  
Delay Times ◽  
Effective Decision

Selecting appropriate and resilient suppliers is an important issue in supply chain management (SCM) literature. Making an effective decision on this issue can decrease external risks and disruptions, purchase costs, and delay times and also guarantees business continuity in the event of disruptions and, consequently, increases company competitiveness and customer satisfaction. This paper aims to provide a model based on identifying and investigating related criteria to evaluate suppliers’ resilience and select the most resilient suppliers in Iran’s electronic industry. To this purpose, the screening technique, the best–worst methodology (BWM), and goal programming (GP) have been applied in the fuzzy environment. The proposed model has been implemented and demonstrated by a case study of the electronic industry, as a real-life example. The results show that agility (0.227), compatibility (0.153), and vulnerability (0.102) are the most important factors for a resilient supplier.

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