This paper addresses the problem of the self-scheduling of thermal generating units during commissioning. A 0/1 mixed-integerlinear formulation is presented, which allows an accurate and realistic modeling for the sc...
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This paper addresses the problem of the self-scheduling of thermal generating units during commissioning. A 0/1 mixed-integerlinear formulation is presented, which allows an accurate and realistic modeling for the scheduling of the commissioning tests that should be performed once the construction of the thermal unit has been completed and prior to entering its commercial operation. A flexible contract between the producer and the contractor regarding the performing period of the commissioning tests is proposed. The model presented can be used by a producer with thermal units in commissioning, who acts either as a price-taker or a price-maker in the day-ahead energy market. Test results on a medium-scale real test system address the effect that the implementation of the proposed model has on the producer profits as well as on the day-ahead market clearing prices.
Mathematical models of complex biological networks are valuable to make predictions on system properties and to identify therapeutic targets. However, development, validation and analysis of predictive models is often...
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Mathematical models of complex biological networks are valuable to make predictions on system properties and to identify therapeutic targets. However, development, validation and analysis of predictive models is often hampered as absolute and quantitative measurement data are rarely available. Instead, the data are typically uncertain with respect to the measured variable or time, relational due to normalization, or data are given as conditional if-then observations. Many common approaches for model development and validation cannot deal with such semi-quantitative data and qualitative information. We present a framework for the guaranteed invalidation and parameter estimation of dynamical models using such data. For this purpose, the data are formally expressed by sets of equalities and inequalities containing binary variables. Then a mixed-integer nonlinear feasibility problem is constructed, which is subsequently relaxed into a mixed-integerlinear program that can be solved efficiently. A model can be proved inconsistent, that is, invalid with the uncertain and semi-quantitative/qualitative data, if the solution set of the mixed-integerlinear program is empty. To exemplify the approach, we analyze different models whether they can show adaptation to a step-input. First, we invalidate all but one model and, second, derive outer-bounds for those regions in the parameter space of the non-invalidated model that contain parameterizations for which it is consistent with the data. Copyright (c) 2012 John Wiley & Sons, Ltd.
Recently, the mixed-model assembly line (MMAL) has been widely studied by many researchers. In fact, there are two basic problems, namely balancing and sequencing problems, which have been investigated in a lot of stu...
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Recently, the mixed-model assembly line (MMAL) has been widely studied by many researchers. In fact, there are two basic problems, namely balancing and sequencing problems, which have been investigated in a lot of studies separately, but few researchers have solved both problems simultaneously. Regarding this, the best results in minimising total utility work have been gained by developing a co-evolutionary genetic algorithm (Co-GA) so far. This paper provides a mixed-integer linear programming (MILP) model to jointly solve the problems. Because of NP-hardness, an evolution strategies (ES) algorithm is presented and evaluated by the same test problems in the literature. Two main hypotheses, namely simultaneous search and feasible search, are tested in the proposed algorithm to improve the quality of solutions. To calibrate the algorithm, a Taguchi design of experiments is employed. The proposed ES is compared with the modified version of Co-GA and the MILP model results. According to numerical experiments and statistical proving, the proposed ES outperformed the modified Co-GA from two points of view: the objective function and the computational time. Additionally, the meta-heuristic algorithms are examined in terms of other well-known criteria in MMAL. Finally, the contribution of each hypothesis in accounting for this superiority is analysed.
In this paper, we study a variant of the resource-constrained project scheduling problem in which resources are flexible, i.e., each resource has several skills. Each activity in the project may need several resources...
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In this paper, we study a variant of the resource-constrained project scheduling problem in which resources are flexible, i.e., each resource has several skills. Each activity in the project may need several resources for each required skill. We present a mixed-integer linear programming formulation for this problem. Several sets of additional inequalities are also proposed. Due to the fact that some of the above-mentioned inequalities require a valid upper bound to the problem, a heuristic procedure is proposed. Computational experience is reported based on randomly generated data, showing that for instances of reasonable size the proposed model enlarged with the additional inequalities can be solved efficiently.
The generation maintenance scheduling problem faced by a power producer aims at defining the optimal time intervals for the maintenance of each generating unit. The planning horizon is typically mid-term (year-ahead)....
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ISBN:
(纸本)9781467308328;9781467308342
The generation maintenance scheduling problem faced by a power producer aims at defining the optimal time intervals for the maintenance of each generating unit. The planning horizon is typically mid-term (year-ahead). In this paper, the annual maintenance scheduling problem of a thermal producer is solved with respect to economic and technical security criteria. The aim is to maximize yearly profit, while simultaneously satisfying the operating constraints of the producer's generating units. Specific constraints regarding unit maintenance are also taken into consideration, such as avoiding the simultaneous planned outage of generating units that belong to the same power station, and maintenance intervals that must be scheduled whenever a specific number of operating hours is completed. The generation maintenance scheduling problem is formulated and solved as a mixed-integer linear programming problem using commercial software (GAMS/CPLEX).
In the current study, the costs and benefits of deploying energy storage system (ESS) are discussed, and the role of ESS in transmission expansion planning (TEP) is investigated. Based on the classical formulation of ...
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ISBN:
(纸本)9781467327299
In the current study, the costs and benefits of deploying energy storage system (ESS) are discussed, and the role of ESS in transmission expansion planning (TEP) is investigated. Based on the classical formulation of TEP, a new formulation is developed considering the simultaneous addition of new circuits and installation of ESS. The fictitious costs of ESS are set instead of actual costs in the proposed model, which can be used to determine the site and size of ESS for transmission investment reduction. The whole formulation is a mixed-integer linear programming problem and can be solved by the well-developed algorithms. The proposed TEP method, which considers the optimal deployment of ESS, has been simulated on three test systems. Test results show the effectiveness of the proposed method and illustrate the potential of installing ESS to reduce network investment costs.
This paper addresses the design of joint source-channel variable-length codes with maximal free distance for given codeword lengths. While previous design methods are mainly based on bounds on the free distance of the...
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ISBN:
(纸本)9780769546568
This paper addresses the design of joint source-channel variable-length codes with maximal free distance for given codeword lengths. While previous design methods are mainly based on bounds on the free distance of the code, the proposed algorithm exploits an exact characterization of the free distance. The code optimization is cast in the framework of mixed-integer linear programming and allows to tackle practical alphabet sizes in reasonable computing time.
Cross-docking plays an important role in supply chain and can reduce delivery lead times, inventory holding and transportation costs. However, the advantages of cross-docking would be reduced without an efficient vehi...
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Cross-docking plays an important role in supply chain and can reduce delivery lead times, inventory holding and transportation costs. However, the advantages of cross-docking would be reduced without an efficient vehicle routing. This paper considers a split vehicle routing problem (SVRP) with capacity constraint for multi-product cross-docks. In VRP with split deliveries (pickups) customers (suppliers) are willing to receive (send) goods in multiple shipments and each node can be served by more than one vehicle. The problem is formulated as a mixed-integer linear programming (MILP) model in the GAMS software to determine the best vehicle routes and the optimal number of utilized vehicles.
The concerns of regulatory authority for the cost efficiency and service quality of distribution utilities has led them to implement monetary schemes, such as penalty/reward mechanism (PRM). PRM provides explicit fina...
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The concerns of regulatory authority for the cost efficiency and service quality of distribution utilities has led them to implement monetary schemes, such as penalty/reward mechanism (PRM). PRM provides explicit financial incentives for distribution system operators (DSO) to maintain or improve their efficiency and quality of service. Although the effectiveness of the PRM is proven, analytical tools that can handle the complex decision-making process faced by decision makers to respond to PRM are scarce. This paper presents an approach for distribution system maintenance management in the presence of the PRM. The proposed approach tailors the maintenance plans by taking into account the equipment condition in terms of failure rate, cost of planned and unplanned outage, as well as labor and material cost in conjunction with the incentives provided by PRM. New insights are also gained regarding the effects of PRM on the process of decision making by DSO.
One of the most challenging tasks in today's food industry is controlling the product quality throughout the food supply chain. In this paper, we integrate food quality in decision-making on production and distrib...
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One of the most challenging tasks in today's food industry is controlling the product quality throughout the food supply chain. In this paper, we integrate food quality in decision-making on production and distribution in a food supply chain. We provide a methodology to model food quality degradation in such a way that it can be integrated in a mixed-integer linear programming model used for production and distribution planning. The resulting model is applied in an illustrative case study, and can be used to design and operate food distribution systems, using both food quality and cost criteria. (C) 2009 Elsevier B.V. All rights reserved.
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