Order allocation among the candidate suppliers plays a basic and critical role in purchasing and supplying management, which is one of the significant subjects in supply chain management. Recently, it has been shown t...
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This paper analyses different charging strategies for a fleet of electric vehicles. Along with increasing the realism of the strategies, the opportunity for acting on the regulating market is also included. We test th...
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Increasing infeed from renewable energy sources poses considerable challenges to system operators (SOs) who are in charge of power system reliability. Accordingly, the frequency of network congestion and the correspon...
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Increasing infeed from renewable energy sources poses considerable challenges to system operators (SOs) who are in charge of power system reliability. Accordingly, the frequency of network congestion and the corresponding congestion management costs have increased dramatically over the last years and give reason to extensively discuss alternative approaches. Among these, flexibility markets bear the potential to complement existing congestion management practices by incentivising decentralised resources with large potentials of flexibility to participate in relieving congestion. For this reason, multiple demonstration projects across Europe are currently testing different flexibility market designs. We contribute to this on-going discussion by investigating the auction design of such a flexibility market. We analytically derive the optimal procurement strategy of a SO within a flexibility market platform, recurring to the well-established methodology of the classical Newsvendor problem and extending it in a stochastic programming framework with two stages. We apply our model to a case study of a transformer that is frequently congested due to high infeed from wind farms. Based on an analysis of relevant sources of flexibility, differentiated concerning lead time and cost structure, we explore the effects of demand uncertainty and information updates between auctions. The results of the case study, including a comprehensive sensitivity analysis, reveal insights that are used to provide policy advice on how to design flexibility procurement markets under specific conditions.
This paper reviews a number of applications of optimization under uncertainty in energy markets resulting from the research project ENSYMORA. A general mathematical formulation applicable to problems of optimization u...
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To achieve the benefits as much as possible, it is required to identify the available PEV capacity and prepare scheduling plans based on that. The analysis revealed that the risk-based scheduling of the microgrid coul...
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Social responsibility is a key factor that could result in success and achieving great benefits for supply chains. Responsiveness and reliability are important social responsibility measures for consumers and all stak...
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Social responsibility is a key factor that could result in success and achieving great benefits for supply chains. Responsiveness and reliability are important social responsibility measures for consumers and all stakeholders that strategists and company managers should be concerned about them in long-term planning horizon. Although, presence of uncertainties as an intrinsic part of supply chains could adversely affect the best set plans by field experts. Accordingly, uncertainty of parameters and uncertainties caused by disruptions should be regarded in planning process of networks to prevent unpredictable negative consequences of such uncertainties for all echelons of supply chain. Based on enumerated matters, the aim of this paper is to design a reliable multi-echelon closed loop supply chain network model that maximizes social responsibility while minimizing fixed establishing and variable processing costs of network design. To cope with uncertainty of parameters, stochastic programming is applied and an effective reliable modelling method is employed to appropriately control unpleasant economic impacts of disruptions. Notably, an efficient robust programming method is applied to give the decision makers the capability to control level of risk-averseness of decisions while modelling uncertain parameters. Finally, the proposed model is solved and its outputs are analyzed on the basis of generated test problems which shows correct performance and applicability of extended model in real world problems.
"Call for Papers – Special Issue on Multidimensional perspectives in Finance and Investment."INFOR: Information Systems and Operational Research, 54(1), pp. 76–77
"Call for Papers – Special Issue on Multidimensional perspectives in Finance and Investment."INFOR: Information Systems and Operational Research, 54(1), pp. 76–77
This paper focuses on addressing uncertainties in disasters when considering lateral transshipment opportunities for pre-positioning relief supplies. To deal with uncertain demands the problem is formulated as a two-s...
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This paper focuses on addressing uncertainties in disasters when considering lateral transshipment opportunities for pre-positioning relief supplies. To deal with uncertain demands the problem is formulated as a two-stage stochastic programming model, which decides simultaneously on the locations of relief facilities and the allocations of relief supplies to demand nodes. Meanwhile, different damage levels caused by disasters are considered and reflected by a survival rate of usable stocked relief items. Multiple types of supplies with various priorities, values and spaces are explored. A real-world case study based on the Gulf Coast region of the United States is conducted to illustrate the application of the developed model. By comparison with the direct shipment solution, the lateral transshipment solution is demonstrated to be more cost-effective and flexible. The sensitivity analysis of out-of-stock penalty cost and maximum travel distance provides managerial insights for relief agencies.
The stochastic nature of wind power generators and their possible outage are crucial issues which make them difficult to participate in electricity markets. However, demand side as a decent balancing resource can be u...
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ISBN:
(纸本)9781538632468
The stochastic nature of wind power generators and their possible outage are crucial issues which make them difficult to participate in electricity markets. However, demand side as a decent balancing resource can be used to compensate the challenges of lack of supply-demand balance or state of outage for wind generators. This paper firstly models the outage of wind generators. Then an offering strategy with a three-stage stochastic programming is presented for a hybrid power plant which includes a wind power producer and a demand response provider. Three electricity markets are considered including day-ahead, adjustment and balancing market. The conditional value-at-risk is also added to the offering strategy to control the profit risk The offering strategy is tested in a wind farm and electricity market located in Spain. The result shows that the hybrid power plant offering strategy can effectively assist with the balancing and outage problem of the wind power producer and increase the overall profit of the joint operation.
This study develops a stochastic Mixed Integer Linear programming (SMILP) model to optimize the reverse logistics network for debris generated from proactive demolition of end-of-life buildings. Unlike most existing r...
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This study develops a stochastic Mixed Integer Linear programming (SMILP) model to optimize the reverse logistics network for debris generated from proactive demolition of end-of-life buildings. Unlike most existing research, this study addresses proactive strategies for the Mitigation stage of disaster management. Our model identifies the optimal number of landfilling areas and sorting facilities, factoring in uncertainties in debris quantity and material quality. It incorporates environmental constraints, such as mandatory sorting processes and recycling thresholds. Multiple scenarios are considered, each with unique parameter values and occurrence probabilities, with the overall objective of minimizing net costs across all scenarios. A realistic case study is used to illustrate the model, demonstrating its capacity to reduce post-disaster recovery costs, improve operational efficiency, and balance financial and environmental considerations. This study offers insights for decision-makers, advocating proactive end-of-life buildings' management as a disaster preparedness and sustainable practices.
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