A bi-level tournament selection method for handling multi-objectives and constraints is provided for low dimensional simplex evolution(LDSE).The idea is general and can apply to other evo utionary algorithms.
A bi-level tournament selection method for handling multi-objectives and constraints is provided for low dimensional simplex evolution(LDSE).The idea is general and can apply to other evo utionary algorithms.
A bi-level tournament selection method for handling multi-objectives and constraints is provided for low dimensional simplex evolution (LDSE).The idea is general and can apply to other evolutionary algorithms.
A bi-level tournament selection method for handling multi-objectives and constraints is provided for low dimensional simplex evolution (LDSE).The idea is general and can apply to other evolutionary algorithms.
This paper presents a mixed-integer optimization approach to the yearly hydrothermal scheduling problem. The proposed method is applied to a hydrothermal system comprising 29 thermal units and 13 hydroplants, includin...
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This paper presents a mixed-integer optimization approach to the yearly hydrothermal scheduling problem. The proposed method is applied to a hydrothermal system comprising 29 thermal units and 13 hydroplants, including 2 pumped storage plants, similar to the Greek Power System. The generation scheduling model is based on an hourly load curve. Perfect competition assumption is adopted and all thermal generators are assumed to bid their marginal cost. A large mixed-integer programming problem is formulated and implemented in GAMS. Binary variables represent thermal unit hourly commitment status. Results on an hourly basis, including thermal unit commitment and dispatch, hydroplant generation and pumping and system marginal price are presented.
Current mixed-integer linear programming solvers are based on linear programming routines that use floating-point arithmetic. Occasionally, this leads to wrong solutions, even for problems where all coefficients and a...
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Current mixed-integer linear programming solvers are based on linear programming routines that use floating-point arithmetic. Occasionally, this leads to wrong solutions, even for problems where all coefficients and all solution components are small integers. An example is given where many state-of-the-art MILP solvers fail. It is then shown how, using directed rounding and interval arithmetic, cheap pre- and postprocessing of the linear programs arising in a branch-and-cut framework can guarantee that no solution is lost, at least for mixed-integer programs in which all variables can be bounded rigorously by bounds of reasonable size.
The capacitated facility location problem (CFLP)is a well-known combinatorial optimization problem with applications in distribution and production planning. It consists in selecting plant sites from a finite set of p...
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The capacitated facility location problem (CFLP)is a well-known combinatorial optimization problem with applications in distribution and production planning. It consists in selecting plant sites from a finite set of potential sites and in allocating customer demands in such a way as to minimize operating and transportation costs. A number of solution approaches based on Lagrangean relaxation and subgradient optimization has been proposed for this problem. Subgradient optimization does not provide a primal (fractional) optimal solution to the corresponding master problem. However, in order to compute optimal solutions to large or difficult problem instances by means of a branch-and-bound procedure information about such a primal fractional solution can be advantageous. In this paper, a (stabilized) column generation method is, therefore, employed in order to solve a corresponding master problem exactly. The column generation procedure is then employed within a branch-and-price algorithm for computing optimal solutions to the CFLP. Computational results are reported for a set of larger and difficult problem instances. (c) 2006 Elsevier B.V. All rights reserved.
In liberalized electricity markets, generation companies bid their hourly generation in order to maximize their profit. The optimization of the generation bids over a short-term weekly period must take into account th...
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In liberalized electricity markets, generation companies bid their hourly generation in order to maximize their profit. The optimization of the generation bids over a short-term weekly period must take into account the action of the competing generation companies and the market-price formation rules and must be coordinated with long-term planning results. This paper presents a three stage optimization process with a data analysis and parameter calculation, a linearized unit commitment, and a nonlinear generation scheduling refinement. Although the procedure has been developed from the experience with the Spanish power market, with minor adaptations it is also applicable to any generation company participating in a competitive market system. (C) 2006 Elsevier Ltd. All rights reserved.
This paper introduces a novel algorithm for selecting the optimal wafers for measurement given a set of selection rules. The algorithm is based on assigning a penalty to each of the sampling rules and then using a mix...
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This paper introduces a novel algorithm for selecting the optimal wafers for measurement given a set of selection rules. The algorithm is based on assigning a penalty to each of the sampling rules and then using a mixed-integer linear program to pick the wafers which minimize the sum of the penalties. By waiting until the metrology step to determine the best wafers to measure, a real-time decision can be made based on which wafers have previously been measured, the tools and chambers on which wafers were processed, and other user-specified selection criteria. The penalties can also be increased after a rule violation to ensure that each of the selection rules are satisfied at a finite frequency.
We present a new formulation for the facility layout problem based on the sequence-pair representation, which is used successfully in VLSI design. By tightening the structure of the problem with this formulation, we h...
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We present a new formulation for the facility layout problem based on the sequence-pair representation, which is used successfully in VLSI design. By tightening the structure of the problem with this formulation, we have extended the solvable solution space from problems with nine departments to problems with eleven departments. (C) 2006 Elsevier B.V. All rights reserved.
In this article we address the production planning of parallel multiproduct batch reactors with sequence-dependent changeovers, a challenging problem that has been motivated by a real-world application of a specialty ...
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In this article we address the production planning of parallel multiproduct batch reactors with sequence-dependent changeovers, a challenging problem that has been motivated by a real-world application of a specialty chemicals business. We propose two production planning models that anticipate the impact of the changeovers in this batch processing problem. The first model is based on underestimating the effects of the changeovers that leads to an MILP problem of moderate size. The second model incorporates sequencing constraints that yield very accurate predictions, but at the expense of a larger MILP problem. To solve large scale problems in terms of number of products and reactors, or length of the time horizon, we propose a decomposition technique based on rolling horizon scheme and also a relaxation of the detailed planning model. Several examples are presented to illustrate the performance of the proposed models. (C) 2007 American Institute of Chemical Engineers.
The forecasted shortage of fossil fuels and the ever-increasing effect of greenhouse gas (GHG) emissions on global warming and environmental stability are two international problems with major technical, economic and ...
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The forecasted shortage of fossil fuels and the ever-increasing effect of greenhouse gas (GHG) emissions on global warming and environmental stability are two international problems with major technical, economic and political implications in the 21st century. Therefore, it is urgent to restructure present energy production and utilization systems in order to ensure that fossil fuels are used with high efficiency and low to zero emissions. Polygeneration energy systems combine power generation and chemical fuel synthesis in a single plant (producing both electricity and fuels) and thus provide a promising alternative pathway towards achieving sustainable and flexible economic development. mixed-integer programming (MIP) is useful in constructing long-term decision models that are suitable for investment planning and design of polygeneration infrastructure systems. This paper presents a model for the investment planning of a polygeneration energy system and a case study addressing a system for production of methanol and electricity in China during the period from 2010 to 2035. It contains five different feedstocks and twelve polygeneration technologies. (C) 2007 Elsevier B.V. All rights reserved.
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