This paper addresses the issues on high operation cost, start up and operation reliability of rapid-start units, such as open cycle gas turbines (OCGTs), for energy scheduling and online/offline reserve allocation in ...
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ISBN:
(纸本)9781424444540
This paper addresses the issues on high operation cost, start up and operation reliability of rapid-start units, such as open cycle gas turbines (OCGTs), for energy scheduling and online/offline reserve allocation in the deregulated electricity market. A probabilistic technique is presented in this paper to assess the un-realised reserve which has been allocated to the rapid-start generators that failed during starting up while considering their response time needed for reserve contribution. This is accomplished by modelling the process in term of expected energy not served (EENS) with an enumerated mathematical formulation. A study on the variation of OCGTs characteristics is performed and the results are compared with those of the 26-thermal unit system from IEEE-RTS integrated with 3 interruptible loads (ILs). Numerical results and discussions documented in this paper may be helpful to provide a guide for economic deployment of rapid-start units for energy and reserve contributions.
We study a production planning problem known as the Discrete Lot-sizing and Scheduling problem with sequence-dependent changeover costs. We consider here the case where there are several identical parallel resources a...
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ISBN:
(纸本)9781424441358
We study a production planning problem known as the Discrete Lot-sizing and Scheduling problem with sequence-dependent changeover costs. We consider here the case where there are several identical parallel resources available for production and we propose solving the resulting optimization problem as a mixed-integer program (MIP) using a commercial solver. This is achieved thanks to the extension of an existing tight MIP formulation for the case of a single resource to the case of parallel resources. The results of our computational experiments show that using the proposed solution approach, we are able to provide guaranteed optimal solutions for instances of medium size with a reasonable computational effort.
This paper addressed the planning and scheduling problem for Earth Observing Satellites Fleet of China. The author first described the problem scope naturally, then proposed a mixed-integer programming model for a sim...
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ISBN:
(纸本)9780769536880
This paper addressed the planning and scheduling problem for Earth Observing Satellites Fleet of China. The author first described the problem scope naturally, then proposed a mixed-integer programming model for a simplified version of the problem, which only considered the data-take activities of the satellites. Then the author gave two heuristic methods for it and made experimental comparisons based on some randomly generated problem instances. Computational Experiments showed that the special conflict-avoided heuristic enjoyed an optimality/computational-time ratio advantage against the other ILOG-based tabu search under a time-critical application background.
Conditional VaR is also called mean excess loss or tail VaR, and CVaR is a coherent measurement of risk. Based on portfolio optimization theory of CVaR put forward by Rockafeller and Uryasev, and combined with Monte C...
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Conditional VaR is also called mean excess loss or tail VaR, and CVaR is a coherent measurement of risk. Based on portfolio optimization theory of CVaR put forward by Rockafeller and Uryasev, and combined with Monte Carlo simulation and branch and bound algorithm, a portfolio optimization model of CVaR is established. The stocks which composed shangzheng 50 index are selected to compose an optimal portfolio under CVaR, mean-variance and VaR measurement. Experiential analysis and comparative experiment have finally shown that the model established in this paper and the method were efficient.
Industrial production processes involving both lot-sizing and cutting stock problems are common in many industrial settings. However, they are usually treated in a separate way, which could lead to costly production p...
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Industrial production processes involving both lot-sizing and cutting stock problems are common in many industrial settings. However, they are usually treated in a separate way, which could lead to costly production plans. In this paper, a coupled mathematical model is formulated and a heuristic method based on Lagrangian relaxation is proposed. Computational results prove its effectiveness. (C) 2009 Elsevier B.V. All rights reserved.
In this paper, a real maintenance workforce scheduling problem is formulated as a multi-objective mixed-integer programming model with the aim of simultaneous minimizing the workforce cost and maximizing the equipment...
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In this paper, a real maintenance workforce scheduling problem is formulated as a multi-objective mixed-integer programming model with the aim of simultaneous minimizing the workforce cost and maximizing the equipment availability. The workforce is provided by the internal and external resources using the regular time, overtime and contracting. The equipment availability is measured using the downtime due to the preventive maintenance (scheduled) and failure repair (unscheduled) jobs. The priority of the imminent or potential failures can be different because of the severity effect of the failures on the system. Hence, the total weighted flow time is used as a scheduling criterion to measure the equipment availability. The proposed model is verified using a comprehensive numerical example and the obtained results are discussed.
We consider a region suffering from irrigation water scarcity. Candidate crops differ widely in their growth cycles, economic values and water consumption. We develop an integrated dynamic programming-mixedinteger pr...
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We consider a region suffering from irrigation water scarcity. Candidate crops differ widely in their growth cycles, economic values and water consumption. We develop an integrated dynamic programming-mixedintegerprogramming model to solve for optimal land exploitation over a one year horizon for multiple crops. The model applies deficit irrigation in order to increase the irrigated area at the expense of reducing crop yield per unit area. The dynamic program (DP) guarantees that deficit irrigation is only considered when it is economically efficient. Moreover, it provides optimal combinations of irrigation levels for each growth stage of candidate crops, accounting for the varying impact of water stress over time and the seasonal supply of irrigation water. The output of the DP serves as input to the mixedinteger program (MIP). The MIP selects the most pro. table crops in the right sequence to benefit the most from the crop-yield dependence on crop predecessor and allocates water and land optimally to maximize total profit. The objective function accounts for the attitude of the decision-maker toward risk by incorporating in its expression a risk-aversion coefficient.
The steady-state economic optimum in chemical process plants generally lies at the intersection of constraints. However, in order to maintain feasible operation in the face of disturbances. the steady-state operating ...
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The steady-state economic optimum in chemical process plants generally lies at the intersection of constraints. However, in order to maintain feasible operation in the face of disturbances. the steady-state operating point needs to be moved some distance from the constraints into the feasible region. The optimal back-off is a function of the plant dynamics, the type and magnitude of the expected disturbances, and the plant control system. This paper considers calculation of the optimal back-off with regulation under constrained predictive control. The resulting optimization problem is multilevel in nature. and is formulated and solved as a mixed-integer quadratic or linear programming problem for which global optimality is guaranteed. Case studies comprising CSTRs in series and a fluid catalytic cracking unit illustrate the application of the strategy. (c) 2007 Elsevier Ltd. All rights reserved.
This paper is concerned with the problem of assigning employees to a number of work centres taking into account employees' expressed preferences for specific shifts, off-days, and work centres. This particular pro...
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This paper is concerned with the problem of assigning employees to a number of work centres taking into account employees' expressed preferences for specific shifts, off-days, and work centres. This particular problem is faced by the Kuwait National Petroleum Corporation that hires a firm to prepare schedules for assigning employees to about 86 stations distributed all over Kuwait. The number of variables in a mixed-integer programming model formulated for this problem is overwhelming, and hence, a direct solution to even the continuous relaxation of this model for relatively large-scale instances is inconceivable. However, we demonstrate that a column generation method, which exploits the special structures of the model, can readily solve the continuous relaxation of the model. Based on this column generation construct, we develop an effective heuristic to solve the problem. Computational results indicate that the proposed approach can facilitate the generation of good-quality schedules for even large-scale problem instances in a reasonable time.
The paper presents a multi-stage stochastic programming formulation for the planning of clinical trials in the pharmaceutical research and development (R&D) pipeline. Scenarios are used to account for the endogeno...
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The paper presents a multi-stage stochastic programming formulation for the planning of clinical trials in the pharmaceutical research and development (R&D) pipeline. Scenarios are used to account for the endogenous uncertainty in clinical trial outcomes. Given a portfolio of potential drugs and limited resources, the model determines the trials to be performed in each planning period and scenario. To reduce the size of the formulation we employ a reduced set of scenarios without compromising the quality of uncertainty representation. Furthermore, we present a number of ideas that allow us to reduce the number of non-anticipativity constraints necessary to model indistinguishable scenarios. The proposed approach is the first stochastic programming formulation to address this problem. (c) 2007 Elsevier Ltd. All rights reserved.
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