In this paper, a probabilistic methodology for estimating the spinning reserve in microgrids is proposed. The spinning reserve amount is determined by maximizing the total profit while considering the unreliability of...
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ISBN:
(纸本)9781424452293
In this paper, a probabilistic methodology for estimating the spinning reserve in microgrids is proposed. The spinning reserve amount is determined by maximizing the total profit while considering the unreliability of units and uncertainties caused by nondispatchable units and load. In order to reduce the computation burden, various uncertainties are aggregated and rounding to an equivalent distribution. The optimization is solved by mixed integer linear programming.
Operations research is usually employed to solve the facility location problem, mainly using mixed integer linear programming (MILP). Meanwhile, some MILP models were not originally designed to solve a large class of ...
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Operations research is usually employed to solve the facility location problem, mainly using mixed integer linear programming (MILP). Meanwhile, some MILP models were not originally designed to solve a large class of location problems, corresponding to those where customers are served in a routing operation. In this case location and routing decisions are strongly interrelated. Moreover, this modeling approach has the difficult of facing a NP-hard problem situation, which means a very high algorithm complexity. Therefore, for large-scale problems the computational times are practically infeasible. This paper has developed an alternative method using a hybrid approach to solve the location problem, taking into account these two aspects: the NP- hard situation and the routing operation. The suggestion is to decompose the problem through a clustering procedure applied to the demand points, followed by the application of an optimization model to each cluster. The proposal appeared to be effective when applied to a set of test problems used on a conducted experiment designed to validate the method.
In this paper we study a new variant of the minimum energy broadcast (MEB) problem, namely the probabilistic MEB (PMEB). The objective of the classic MEB problem is to assign transmission powers to the nodes of a wire...
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In this paper we study a new variant of the minimum energy broadcast (MEB) problem, namely the probabilistic MEB (PMEB). The objective of the classic MEB problem is to assign transmission powers to the nodes of a wireless network is such a way that the total energy dissipated on the network is minimized, while a connected broadcasting structure is guaranteed by the assigned transmission powers. In the new variant of the problem treated in this paper, node failure is taken into account, aiming at providing solutions with a chosen reliability level for the broadcasting structure. Three mixed integer linear programming formulations for the new problem are presented, together with efficient formulation-dependent methods for their solution. Computational results are proposed and discussed. One method emerges as the most promising one under realistic settings. It is able to handle problems with up to fifty nodes. (C) 2007 Elsevier B.V. All rights reserved.
Compressor selection is one of the primary functions in operation of natural gas pipelines, and a major concern of the task is to minimize operating costs. This study presents a comparison of three automation techniqu...
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Compressor selection is one of the primary functions in operation of natural gas pipelines, and a major concern of the task is to minimize operating costs. This study presents a comparison of three automation techniques for compressor selection: mixed integer linear programming. genetic algorithms, and expert systems. In compressor selection, dispatchers often turn on/off compressor units based on the status of the pipeline and the anticipated customer demand. Since a novice dispatcher often performs this task on a trial-and-error basis without any guarantee of optimal operations, it is desirable to develop a decision support system that can select compressors based on the available data. This study presents a comparison of three automation techniques for incorporation into a decision support system. Based on parameter values for one section of the gas pipeline at the St. Louis East area in Saskatchewan, Canada, a comparison of the strengths and weaknesses of the three automation techniques as well as the recommendations they gave are discussed. (c) 2007 Elsevier Ltd. All rights reserved.
Enterprise optimisation can rapidly strip significant "bottom line" costs out of global operations, giving companies a real competitive edge. The benefits of managing supply chain networks by integrating ope...
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Enterprise optimisation can rapidly strip significant "bottom line" costs out of global operations, giving companies a real competitive edge. The benefits of managing supply chain networks by integrating operational, design and financial decisions have been acknowledged by the industrial and academic community. The objective of this work is to determine the optimal configuration of a production and distribution network subject to operational and financial constraints. Operational constraints include quality, production and supply restrictions, and are related to the allocation of the production and the work-load balance. Financial constraints include production costs, transportation costs and duties for the material flowing within the network subject to exchange rates. As a business decision the out-sourcing of production is considered whenever the organisation cannot satisfy the demand. A mixed integer linear programming (MILP) model is proposed to describe the optimisation problem. A case study for the coatings business unit of a global specialty chemicals manufacturer is used to demonstrate the applicability of the approach in a number of scenarios. (c) 2007 Elsevier B.V. All rights reserved.
A two-stage algorithm based on branch-and-cut is proposed to solve the unit commitment (UC) problem. At first, the primal UC problem is reformulated as a simple mixedinteger quadratic programming (MIQP), then the MIQ...
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ISBN:
(纸本)9781424426294
A two-stage algorithm based on branch-and-cut is proposed to solve the unit commitment (UC) problem. At first, the primal UC problem is reformulated as a simple mixedinteger quadratic programming (MIQP), then the MIQP is solved by the commercial software CPLEX. In stage I of the implementation of the algorithm, a mixed integer linear programming is solved to get its optimal or feasible solution. In stage II, the MIQP is solved starting from the solution obtained in stage I. The computation time of solving MIQP can be saved remarkably with our two-stage method than with the direct method. The simulation results for 6 systems from 10 to 100 units show that the proposed method is efficient for large scale UC problems. Especially, the proposed method can achieve good near-optimal solutions.
This study presents a method for the design of a hydrogen infrastructure system including production, storage and transportation of hydrogen. We developed a generic optimization-based model to support the decision-mak...
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This study presents a method for the design of a hydrogen infrastructure system including production, storage and transportation of hydrogen. We developed a generic optimization-based model to support the decision-making process for the design of the hydrogen supply chain. The network design problem is formulated as a mixed integer linear programming (MILP) problem to identify the optimal supply chain configurations from various alternatives. The objective is to consider not only cost efficiency, but also safety. Since there is a trade-off between these two objectives, formal multiobjective optimization techniques are required to establish the optimal Pareto solutions that can then be used for decision-making purposes. With the model, the effects of demand uncertainty can be also analyzed by comparing the deterministic and the stochastic solutions. The features and capabilities of the model are illustrated through the application of future hydrogen infrastructure of Korea. The optimal Pareto solutions utilize both cost-oriented and safety-oriented strategies. (C) 2008 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved.
This paper proposes a mixedintegerlinear program (MILP) for the design and planning of a production-distribution system. This study aims to help strategic and tactical decisions: opening, closing or enlargement of f...
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This paper proposes a mixedintegerlinear program (MILP) for the design and planning of a production-distribution system. This study aims to help strategic and tactical decisions: opening, closing or enlargement of facilities, supplier selection, flows along the supply chain. These decisions are dynamic, i.e. the value of the decision variables may change within the planning horizon. The model considers a multi-echelon, multi-commodity production-distribution network with deterministic demands. We present one application: how to plan the expansion of a company that has to face increasing demands. We report numerical experiments with an MILP solver. (C) 2008 Elsevier B.V. All rights reserved.
Passengers travelling in public transportation networks often have to use different lines to cover the trip from their origin to the desired destination. As a consequence, the reliability of connections between vehicl...
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Passengers travelling in public transportation networks often have to use different lines to cover the trip from their origin to the desired destination. As a consequence, the reliability of connections between vehicles is a key issue for the attractiveness of the intermodal transportation network and it is strongly affected by some unpredictable events like breakdowns or vehicle delays. In such cases, a decision is required to determine if the connected vehicles should wait for the delayed ones or keep their schedule. The delay management problem (DMP) consists in defining the wait/depart policy which minimizes the total delay on the network. In this work, we present two equivalent mixed integer linear programming models for the DMP with a single initial delay, able to reduce the number of variables with respect to the formulations proposed by the literature. The two models are solved by a branch and cut procedure and by a constraint generation approach respectively, and preliminary computational results are presented. (C) 2006 Elsevier B.V. All rights reserved.
Signal transduction is an important process that controls cell proliferation, metabolism, differentiation, and so on. Effective computational models which unravel such a process by taking advantage of high-throughput ...
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Signal transduction is an important process that controls cell proliferation, metabolism, differentiation, and so on. Effective computational models which unravel such a process by taking advantage of high-throughput genomic and proteomic data are highly demanded to understand the essential mechanisms underlying signal transduction. Since protein-protein interaction (PPI) plays an important role in signal transduction, in this paper, we present a novel method for modeling signaling pathways from PPI networks automatically. Given an undirected weighted protein interaction network, finding signaling pathways is treated as searching for optimal subnetworks according to some cost function. To cope with this optimization problem, a network flow model is proposed in this work to extract signaling pathways from protein interaction networks. In particular, the network flow model is formalized and solved as a mixed integer linear programming (MILP) model, which is simple in algorithm and efficient in computation. The numerical results on two known yeast MAPK signaling pathways demonstrate the efficiency and effectiveness of the proposed method.
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