Integrating inventory and transportation decisions is vital in supply chain management and can enable decision-makers to achieve competitive advantages. This study considers a multi-item replenishment problem (MIRP) w...
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Integrating inventory and transportation decisions is vital in supply chain management and can enable decision-makers to achieve competitive advantages. This study considers a multi-item replenishment problem (MIRP) with a piece-wise linear transportation cost under demand uncertainty, which usually occurs both in retail and production environment when several items must be ordered from a single supplier. Conventionally, two-stage stochastic programming formulation is risk-neutral, and it lacks robustness in the presence of high data variability. Hence, we introduce the Conditional Value at Risk (CVaR) approach for MIRP. Additionally, we deploy both single and multi-cut L-shaped and the sampleaverage approximation method to circumvent the computational complexity to solve large-scale instances. The data-driven simulation study is used to benchmark the results from deterministic, risk-neutral, and risk-averse stochastic models. The results indicate that under higher data variations, the risk-averse model provides better perspectives for a decision-maker. The results show a 40-50% reduction in lost sales with marginal growth in total cost while considering CVaR instead of a risk-neutral approach.
This study considers ISO day-ahead (DA) scheduling under uncertain conditions with demand response (DR). Two kinds of DR, incentive-based DR (IDR) and price-based DR (PDR) are both incorporated according to their resp...
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This study considers ISO day-ahead (DA) scheduling under uncertain conditions with demand response (DR). Two kinds of DR, incentive-based DR (IDR) and price-based DR (PDR) are both incorporated according to their response characteristics. A bi-level two-stage stochastic security-constrained unit commitment (SCUC) model is proposed for this programme to minimise the ISO cost considering uncertain wind power output and uncertain price elasticity. The upper level is a two-stage stochastic programme. The first stage determines unit commitment and contract capacity of IDR programme while the second stage determines economic dispatch, wind power utilisation and actual dispatch power of IDR programme in the real-time (RT). A chance-constraint is used to ensure wind power utilisation. In the lower level, a priority method is used to select successful bidders based on the calculated contract capacity from the upper level. Results on the revised IEEE 118-bus system show that, the ISO would avoid frequent rescheduling and economic loss with uncertain PDR incorporated into the model. Besides, with IDR flexibly mitigating uncertainty and volatility from wind power and PDR, the ISO would have lower cost and avoid frequent rescheduling of thermal units. Also, this model could ensure wind power utilisation, thus promoting wind power integration.
A novel approach is proposed that exploits the use of a flexible recipe framework as a better way to handle the risk associated with the scheduling under uncertainty of batch chemical plants. The proposed solution str...
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A novel approach is proposed that exploits the use of a flexible recipe framework as a better way to handle the risk associated with the scheduling under uncertainty of batch chemical plants. The proposed solution strategy relies on a novel two-stage stochastic formulation that explicitly includes the trade-off between risk and profit at the decision-making level. The model uses a continuous-time domain representation and the generalized notion of precedence. Management of risk is explicitly addressed by including a control measure (i.e., the profit in the worst scenario), as an additional objective to be considered, thus, leading to a multiobjective optimization problem. To overcome the numerical difficulties associated with such mathematical formulation, a decomposition strategy based on the sampleaverage approximation (SAA) is introduced. The main advantages of this approach are illustrated through a case study, in which a set of solutions appealing to decision makers with different attitudes toward risk are obtained. The potential benefits of the proposed flexible recipe framework as a way of managing the risk associated with the plant operation under demand uncertainty are highlighted through comparison with the conventional approach that considers nominal operating conditions. Numerical results corroborate the advantages of exploiting the capabilities of the proposed flexible recipe framework for risk management purposes. (c) 2008 American Institute of Chemical Engineers.
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