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.
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.
Humanitarian organizations, mandated with responding to emergencies, generally provide food assistance via in-kind and/or cash transfers. Although cash and in-kind transfers have had varying effects across different r...
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Humanitarian organizations, mandated with responding to emergencies, generally provide food assistance via in-kind and/or cash transfers. Although cash and in-kind transfers have had varying effects across different regions, the superiority of one over the other has been debated. This study considers a mixed strategy that includes both cash and in-kind transfer in the presence of finite budget, given a slow-onset disaster such as famine or drought. Importantly, it proposes an evidence-based framework based on the given data. Specifically, a two-stage stochastic program with recourse is proposed, where uncertainty stems from the slow-onset disaster that has non-uniform impact across a given geographical region. The proposed program is first used to study the slow-onset disaster situation in Kenya, and then to evaluate the performance of the cash versus in-kind transfer programs. We also solved larger size problem instances using the sample average approximation (SAA) algorithm, and the resulting analyses underscore the deductions of the case study that although cash transfer is more efficient than in-kind transfer, however, the latter is inevitable due to local unavailability of certain commodities.
We model simple and novel three-player bi-form coalitional games to analyse community energy projects in Chile and Scotland. We take into account two methods based on biform games, which deal with games with a non-emp...
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We model simple and novel three-player bi-form coalitional games to analyse community energy projects in Chile and Scotland. We take into account two methods based on biform games, which deal with games with a non-empty Core and an empty Core, respectively, and construct models based on real-world data on community energy projects, net billing (or distributed generation) schemes, and ordinary utility contracts. We then use these to derive insights about the economic-strategic viability of community energy projects, in the sense of stability within the projects or coalitions and competitiveness versus the other schemes. Under some mild assumptions, we find that community energy projects can be the best strategy to follow for residential electricity customers in Scotland and Chile. Cost subsidisation can further improve community energy incentives. Moreover, after a statistical simulation, we find that community energy projects present more opportunities to be implemented in comparison with net billing schemes in both countries. We use these results to draw conclusions for the community energy sector and show that biform games can be a valuable tool to analyse increasingly complex electricity markets. (C) 2020 Elsevier B.V. All rights reserved.
From the point of view of quality management, it is an important issue to develop some performance indexes for a flow network. This paper studies the performance indexes for a stochastic-flow network in which each arc...
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From the point of view of quality management, it is an important issue to develop some performance indexes for a flow network. This paper studies the performance indexes for a stochastic-flow network in which each arc has several possible capacities. For the case that multiple types of commodity are transmitted through the same stochastic-flow network, this paper defines the system capacity as a vector and then proposes a new performance index. An algorithm in terms of minimal cuts is proposed to evaluate such a performance index.
Disassembly Line Balancing Problem considered here both chooses the best disassembly alternative for an end of life product and assigns the corresponding disassembly tasks to the workstations of the line with the aim ...
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Disassembly Line Balancing Problem considered here both chooses the best disassembly alternative for an end of life product and assigns the corresponding disassembly tasks to the workstations of the line with the aim to reduce the line cost. Precedence and cycle time constraints are observed. Task times are assumed stochastic with known normal probability distributions. The line cost includes the investment and operation costs for workstations as well as penalty costs generated by the cycle time constraints violations. To deal with uncertainties, a stochastic linear mixed integer formulation is developed. To solve efficiently the problem, L-shaped algorithm combined with Latin Hypercube Sampling is proposed.
Electricity retailers face increasing uncertainty due to the ongoing expansion and self-consumption ofunpredictable distributed generation in the residential sector. We analyze how increasing levels of households'...
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Electricity retailers face increasing uncertainty due to the ongoing expansion and self-consumption ofunpredictable distributed generation in the residential sector. We analyze how increasing levels of households'solar PV self-generation affect the short-term decision-making and associated risk exposure of electricityretailers in the German day-ahead and intraday markets. First, we develop a stochastic model accountingfor correlations between solar load, residual load and price in sequentially nested wholesale spot marketsacross seasons and type of day. Second, we develop a computationally tractable two-stage stochastic mixed-integer optimization model to investigate the trading portfolio and risk optimization problem faced by *** conditional value-at-risk we assess the retailers' profitability and risk exposure to different levels ofPV self-generation by assuming different retail tariff schemes. We find risk-hedging trading strategies andtariffs to have greater impact in Summer and with low levels of residual load in the system, i.e. when thesolar generation uncertainty affects more the households' demand to be served and the wholesale spot *** study is innovative in unveiling the potential of dynamic electricity tariffs, which are indexed to spotprices, to sustain a high penetration of renewable energy source while promoting a fair risk sharing betweenretailers, regular consumers and prosumers (consumers with self-generation). Our findings have implicationsfor electricity retailers facing load and revenue risks in wholesale spot markets, likewise for regulators andpolicy-makers interested in electricity market design.
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