If CO2 capture and storage (CCS) is to become a viable option for low-carbon power generation, its deployment will require the construction of dedicated CO2 transport infrastructure. This paper describes the InfraCCS ...
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If CO2 capture and storage (CCS) is to become a viable option for low-carbon power generation, its deployment will require the construction of dedicated CO2 transport infrastructure. This paper describes the InfraCCS model, which can determine the likely extent and cost of the optimal least-cost CO2 transport network at European scale for the period 2015-2050, with 2015 the earliest foreseeable starting date of the CCS projects co-funded by the European Energy Programme for Recovery (EEPR), and 2050 the EU's target date for 80-95% reduction of greenhouse gas emissions. The computation is made possible by a number of methodological innovations compared to previous research, in particular: the use of k-means clustering to reduce the number of nodes in the network;the application of the Delaunay triangulation algorithm for pipeline pre-selection;and the introduction of a mathematically convenient yet realistic new pipeline costing model. The InfraCCS tool is applied to determine the optimal network corresponding to a CCS scenario that ensures near-complete decarbonisation of the European power sector. It is shown that the size of the CO2 network could range from 11,000 to 17,000 km by 2050, requiring 16-36 billion euros investment, with the higher numbers corresponding to the case when onshore aquifers are excluded as potential CO2 storage sites. Since the model shows that by 2030 more than half of the EU Member States could be involved in cross-border CO2 transport, international coordination seems crucial for the development of an optimised trans-European CO2 transport network. (C) 2011 Elsevier Ltd. All rights reserved.
In this paper a different type II robotic assembly line balancing problem (RALB-II) is considered. One of the two main differences with the existing literature is objective function which is a multi-objective one. The...
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In this paper a different type II robotic assembly line balancing problem (RALB-II) is considered. One of the two main differences with the existing literature is objective function which is a multi-objective one. The aim is to minimize the cycle time, robot setup costs and robot costs. The second difference is on the procedure proposed to solve the problem. In addition, a new mixed-integer linear programming model is developed. Since the problem is NP-hard, three versions of multi-objective evolution strategies (MOES) are employed. Numerical results show that the proposed hybrid MOES is more efficient. (C) 2011 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
A distribution case pack contains an assortment of varying quantities of different stock keeping units (SKUs) packed in a single box or pallet, with a goal of reducing handling requirements in the distribution chain. ...
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A distribution case pack contains an assortment of varying quantities of different stock keeping units (SKUs) packed in a single box or pallet, with a goal of reducing handling requirements in the distribution chain. This article studies case pack procurement planning problems that address the trade-off between reduced order handling costs and higher inventory-related costs under dynamic, deterministic demand. The properties of optimal solutions for special cases of the problem involving one and two case packs are first established and these properties are used to solve the problem via dynamic programming. For the general model with multiple predefined case packs, which is shown to be strongly NP-hard, the exact approach is generalized to solve the problem in pseudopolynomial time for a fixed number of case packs. In addition, for large-size problems, the problem formulation is strengthed using valid inequalities and a family of heuristic solutions is designed. Computational tests show that these heuristic approaches performvery well compared to the commercial mixed-integerprogramming solver CPLEX. In addition to providing detailed methods for solving problems with deterministic demand, strategies for addressing problems with uncertain demands are discussed.
In spite of many studies, investigating balancing and sequencing problems in mixed-Model Assembly Line (MMAL) individually, this paper solves them simultaneously aiming to minimize total utility work. A new mixed-Inte...
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In spite of many studies, investigating balancing and sequencing problems in mixed-Model Assembly Line (MMAL) individually, this paper solves them simultaneously aiming to minimize total utility work. A new mixed-integer linear programming (MILP) model is developed to provide the exact solution of the problem with station-dependent assembly times. Because of NP-hardness, a Simulated Annealing (SA) is applied and compared to the Co-evolutionary Genetic Algorithm (Co-GA) from the literature. To strengthen the search process, two main hypotheses, namely simultaneous search and feasible search, are developed contrasting Co-GA. Various parameters of SA are reviewed to calibrate the algorithm by means of Taguchi design of experiments. Numerical results statistically show the efficiency and effectiveness of the proposed SA in terms of both the quality of solution and the time of achieving the best solution. Finally, the contribution of each hypothesis in this superiority is analyzed. (c) 2011 Elsevier B.V. All rights reserved.
A new problem called lot sizing with supplier selection problem in the multi-product multi-echelon defective supply chain network (MDSCN) is proposed in this study. We explain the problem by a case study. We take the ...
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A new problem called lot sizing with supplier selection problem in the multi-product multi-echelon defective supply chain network (MDSCN) is proposed in this study. We explain the problem by a case study. We take the multi-product MDSCN of X enterprise into account. Back and front engine blocks are products of X enterprise. The aim of this study is to identify how many components will be purchased from which supplier while meeting the demands of the customers for these two products. The supply chain (SC) network of X enterprise is formed by mixed-integer linear programming (MILP). The optimization of current SC network of X enterprise is carried out by using linear, INeractive, Discrete Optimizer (LINDO) program. The customer expectations of X enterprise are met at the highest level, and it gives the opportunity to have the knowledge, which reduces the total cost, of purchasing-production-distribution strategy with this work.
Assessing the environmental performance of hydrogen infrastructures is essential for determining their practical viability. Previous optimization approaches for hydrogen networks have focused on optimizing a single en...
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Assessing the environmental performance of hydrogen infrastructures is essential for determining their practical viability. Previous optimization approaches for hydrogen networks have focused on optimizing a single environmental metric in conjunction with the economic performance. This approach is inadequate as it may leave relevant environmental criteria out of the analysis. We propose herein a novel framework for optimizing hydrogen supply chains (SC) according to several environmental indicators. Our method comprises two steps. In step one, we formulate a multi-objective mixed-integerlinear program (MILP) that accounts for the simultaneous minimization of the most relevant life cycle assessment (LCA) impacts. Principal Component Analysis (PCA) is next employed in the post-optimal analysis of the MILP in order to facilitate the interpretation and analysis of its solution space. We demonstrate the capabilities of this approach through its application to the design of the future (potential) hydrogen SC in Spain. Copyright (C) 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.
In this paper we study the problem of replicating the performances of a stock market index, i.e. the so-called index tracking problem, and the problem of out-performing a market index, i.e. the so-called enhanced inde...
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In this paper we study the problem of replicating the performances of a stock market index, i.e. the so-called index tracking problem, and the problem of out-performing a market index, i.e. the so-called enhanced index tracking problem. We introduce mixed-integer linear programming (MILP) formulations for these two problems. Furthermore, we present a heuristic framework called Kernel Search. We analyze and evaluate the behavior of several implementations of the Kernel Search framework to the solution of the index tracking problem. We show the effectiveness and efficiency of the framework comparing the performances of these heuristics with those of a general-purpose solver. The computational experiments are carried out using benchmark and newly created instances. (C) 2011 Elsevier B.V. All rights reserved.
A decision support tool helping the transmission system operator (TSO) dispatchers to minimize the costs for the load-frequency control is proposed in this paper. Dispatch of tertiary control reserves is done primaril...
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A decision support tool helping the transmission system operator (TSO) dispatchers to minimize the costs for the load-frequency control is proposed in this paper. Dispatch of tertiary control reserves is done primarily with an aim to ensure secure operation of the transmission system, while the costs associated with utilization of the control reserves are traditionally of less importance. The mixed-integer linear programming based optimization tool proposed in this paper suggests such activation of tertiary control reserves which minimizes the costs for the control reserves utilization and ensures secure operation of the transmission system at the same time. Through a case study comparing the control based on the decision support tool with historical control performed manually by the TSO dispatchers, it is demonstrated that the costs for the load-frequency control could be reduced. (c) 2012 Elsevier Ltd. All rights reserved.
This paper presents a mixed-integer linear programming model for the solution of the centralized Generation Expansion Planning (GEP) problem. The GEP objective is the minimization of the total present value of investm...
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This paper presents a mixed-integer linear programming model for the solution of the centralized Generation Expansion Planning (GEP) problem. The GEP objective is the minimization of the total present value of investment, operating and unserved energy costs net the remaining value of the new units at the end of the planning horizon. Environmental considerations are modeled through the incorporation of the cost of purchasing emission allowances in the units' operating costs and the inclusion of annual renewable quota constraints and penalties. A monthly time-step is employed, allowing mid-term scheduling decisions, such as unit maintenance scheduling and reservoir management, to be taken along with investment decisions within the framework of a single long-term optimization problem. The proposed model is evaluated using a real (Greek) power system. Sensitivity analysis is performed for the illustration of the effect of demand, fuel prices and CO2 prices uncertainties on the planning decisions. (C) 2011 Elsevier B.V. All rights reserved.
New mixed-integer linear programming formulations are presented for the quadratic assignment problem, based on splittings of the coefficient matrices. Computational results are reported for medium-sized problem instan...
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New mixed-integer linear programming formulations are presented for the quadratic assignment problem, based on splittings of the coefficient matrices. Computational results are reported for medium-sized problem instances in the QAPLIB collection. (c) 2012 Elsevier Ltd. All rights reserved.
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