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Single item lot-sizing with non-decreasing capacities

MATHEMATICAL programming 2010年第1期121卷 123-143页

作者： Pochet, Yves Wolsey, Laurence A. Catholic Univ Louvain CORE B-1348 Louvain Belgium Catholic Univ Louvain INMA Dept Engn Math B-1348 Louvain Belgium Catholic Univ Louvain IAG LSM Louvain Sch Management B-1348 Louvain Belgium

We consider the single item lot-sizing problem with capacities that are non-decreasing over time. When the cost function is (i) non-speculative or Wagner-Whitin (for instance, constant unit production costs and non-negative unit holding costs) and (ii) the production set-up costs are non-increasing over time, it is known that the minimum cost lot-sizing problem is polynomially solvable using dynamic programming. When the capacities are non-decreasing, we derive a compact mixed integer programming reformulation whose linear programming relaxation solves the lot-sizing problem to optimality when the objective function satisfies (i) and (ii). The formulation is based on mixing set relaxations and reduces to the (known) convex hull of solutions when the capacities are constant over time. We illustrate the use and potential effectiveness of this improved LP formulation on a few test instances, including instances with and without Wagner-Whitin costs, and with both non-decreasing and arbitrary capacities over time.

关键词： Lot-Sizing Mixing set relaxation Compact reformulation Production planning mixed integer programming

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Energy-Efficient Buildings Facilitated by Microgrid

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IEEE TRANSACTIONS ON SMART GRID 2010年第3期1卷 243-252页

作者： Guan, Xiaohong Xu, Zhanbo Jia, Qing-Shan Xi An Jiao Tong Univ SKLMS Lab Xian 710049 Peoples R China Xi An Jiao Tong Univ MOE KLINNS Lab Xian 710049 Peoples R China Tsinghua Univ Ctr Intelligent & Networked Syst CFINS TNLIST Beijing 100084 Peoples R China

Recent research shows that 20%-30% of building energy consumption can be saved through optimized operation and management without changing the building structure and the hardware configuration of the energy supply system. Therefore, there is a huge potential for building energy savings through efficient operation. Microgrid technology provides an opportunity and a desirable infrastructure for improving the efficiency of energy consumption in buildings. The key to improve building energy efficiency in operation is to coordinate and optimize the operation of various energy sources and loads. In this paper, the scheduling problem of building energy supplies is considered with the practical background of a low energy building. The objective function is to minimize the overall cost of electricity and natural gas for a building operation over a time horizon while satisfying the energy balance and complicated operating constraints of individual energy supply equipment and devices. The uncertainties are captured and their impact is analyzed by the scenario tree method. Numerical testing is performed with the data of the pilot low energy building. The testing results show that significant energy cost savings can be achieved through integrated scheduling and control of various building energy supply sources. It is very important to fully utilize solar energy and optimize the operation of electrical storage. It is also shown that precooling is a simple way to achieve energy savings.

关键词： Energy saving integrated building control mixed integer programming

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Location of a biomass based methanol production plant: A dynamic problem in northern Sweden

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APPLIED ENERGY 2010年第1期87卷 68-75页

作者： Leduc, S. Lundgren, J. Franklin, O. Dotzauer, E. Int Inst Appl Syst Anal A-2361 Laxenburg Austria Lulea Univ Technol Div Energy Engn SE-97187 Lulea Sweden Malardalen Univ SE-72123 Vasteras Sweden

Concerning production and use of biofuels, mismatch between the locations of feedstock and the biofuel consumer may lead to high transportation costs and negative environmental impact. In order to minimize these consequences, it is important to locate the production plant at an appropriate location. In this a case study of the county of Norrbotten in northern Sweden is presented with the purpose to illus-paper, trate how an optimization model could be used to assess a proper location for a biomass based methanol production plant. The production of lignocellulosic based methanol via gasification has been chosen, as methanol seems to be one promising alternative to replace fossil gasoline as an automotive fuel and Norrbotten has abundant resources of woody biomass. If methanol would be produced in a stand-alone production plant in the county, the cost for transportation of the feedstock as well as the produced methanol would have great impact on the final cost depending on where the methanol plant is located. Three different production plant sizes have been considered in the study, 100, 200 and 400 MW (biomass fuel input), respectively. When assessing a proper location for this kind of plant, it is important to also consider the future motor fuel demand as well as to identify a heat sink for the residual heat. In this study, four different automotive fuel- and district heating demand scenarios have been created until the year 2025. The results show that methanol can be produced at a maximum cost of 0.48 (sic)/1 without heat sales. By selling the residual heat as district heating, the methanol production cost per liter fuel may decrease by up to 10% when the plant is located close to an area with high annual heat demand. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Plant location Methanol Forestry-based biomass Gasification Heat mixed integer programming

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Min-degree constrained minimum spanning tree problem: New formulation via Miller-Tucker-Zemlin constraints

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COMPUTERS & OPERATIONS RESEARCH 2010年第1期37卷 72-82页

作者： Akgun, Ibrahim Tansel, Barbaros C. Bilkent Univ Dept Ind Engn TR-06800 Ankara Turkey

Given an undirected network with positive edge costs and a positive integer d > 2, the minimum-degree constrained minimum spanning tree problem is the problem of finding a spanning tree with minimum total cost such that each non-leaf node in the tree has a degree of at least d. This problem is new to the literature while the related problem with upper bound constraints on degrees is well studied. mixed-integer programs proposed for either type of problem is composed, in general, of a tree-defining part and a degree-enforcing part. In our formulation of the minimum-degree constrained minimum spanning tree problem, the tree-defining part is based on the Miller-Tucker-Zemlin constraints while the only earlier paper available in the literature on this problem uses single and multi-commodity flow-based formulations that are well studied for the case of upper degree constraints. We propose a new set of constraints for the degree-enforcing part that lead to significantly better solution times than earlier approaches when used in conjunction with Miller-Tucker-Zemlin constraints. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： mixed integer programming Degree-enforcing constraints Miller-Tucker-Zemlin constraints Minimum spanning tree Flow formulation Rooted arborescence

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Optimum service capacity and demand management with price incentives

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2010年第2期204卷 316-327页

作者： Ozluk, Ozgur Elimam, Abdelghani A. Interaminense, Eduardo Amer Univ Cairo Dept Mech Engn Sch Sci & Engn Cairo Egypt San Francisco State Univ Coll Business Dept Decis Sci San Francisco CA 94132 USA MCI San Francisco CA 94105 USA

Service firms periodically face fluctuating demand levels. They incur high costs to handle peak demand and pay for under-utilized capacity during low demand periods. In this paper, we develop a mixed integer programming (MIP) model based on the real life experience of a Brazilian telecommunications firm. The model determines the optimum staffing requirements with different seniority levels for employees, as well as the distribution and balancing of workload utilizing flexibility of some customers in their service completion day. The proposed MIP uses monetary incentives to smooth the workload by redistributing some of the peak demand, thereby increasing capacity utilization. Due to the intractable nature of optimizing the proposed MIP model, we present a heuristic solution approach. The MIP model is applied to the case of the examined Brazilian Telecommunications firm. The computational work on this base case and its extensions shows that the proposed MIP model is of merit, leading to approximately seventeen percent reduction in the base case operating costs. Extensive computational work demonstrates that our heuristic provides quality solutions in very short computational times. The model can also be used to select new customers based on the workload, the revenue potential of these new customers and their flexibility in accepting alternate service completion dates. The generic structure of the proposed approach allows for its application to a wide variety of service organizations facing similar capacity and demand management challenges. Such wide applicability enhances the value of our work and its expected benefits. (C) 2009 Elsevier B.V. All rights reserved.

关键词： mixed integer programming Workload smoothing Delivery dates Heuristics Incentives

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A decision support framework for global supply chain modelling: an assessment of the impact of demand, supply and lead-time uncertainties on performance

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2010年第11期48卷 3245-3268页

作者： Acar, Yavuz Kadipasaoglu, Sukran Schipperijn, Peter Bahcesehir Univ Fac Econ & Adm Sci Istanbul Turkey Bogazici Univ Istanbul Turkey Energy Technol Co Houston TX 77042 USA

We developed a decision support framework for a global manufacturer of specialty chemicals to study the relative impact of demand, supply and lead-time uncertainties on cost and customer service performance. Our approach combines optimisation and simulation methodologies as follows: mathematical models provide optimal plans via a novel approach to the supply chain planning mechanism of the Company. Simulation models execute the supply chain plans so as to allow the examination of the outcomes under the various sources of uncertainty. The iterative use of optimisation and simulation methodologies allows the user the benefit of obtaining optimal solutions while revealing the impact of uncertainties on system performance. Our results indicate that demand uncertainty has the greatest negative impact on performance for the supply chain that we modelled in this study, emphasising the importance of effective forecasting. The relative importance of supply and lead-time uncertainties varies according to the performance measures. While our results are valid for the specific supply chain and the operating environment we modelled, our study emphasises the importance of the ability to model supply chains realistically to obtain valid and useful results.

关键词： supply chain modelling uncertainty simulation mixed integer programming

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Robust train formation planning

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART F-JOURNAL OF RAIL AND RAPID TRANSIT 2010年第F2期224卷 75-90页

作者： Shafia, M. A. Sadjadi, S. J. Jamili, A. IUST Dept Ind Engn Tehran Iran

Train formation planning models determine the routing and frequency of trains and assign the wagons to trains. In this article, a new robust mixed integer model for the train formation problems is proposed where the input data are subject to uncertainty. The optimal solution of the proposed model of this article is believed to be difficult to determine and a heuristic approach to find the near-optimal solution is presented. The implementation of the proposed model of this article is demonstrated for a real-world case study and the results are discussed.

关键词： train formation problem robust approach perturbation mixed integer programming heuristic algorithm

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A mixed integer approach for time-dependent gas network optimization

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OPTIMIZATION METHODS & SOFTWARE 2010年第4期25卷 625-644页

作者： Mahlke, D. Martin, A. Moritz, S. Tech Univ Darmstadt FG Optimizat D-64289 Darmstadt Germany

A gas network consists of pipes to transport the gas from the suppliers to the consumers. Due to friction with the pipe walls, gas pressure gets lost. Compressors compensate this pressure loss at the cost of consuming fuel gas. The aim of gas network optimization is to minimize the fuel gas consumption of the compressors in such a way that the contracts with consumers and suppliers are fulfilled. This problem leads to a very complex mixed integer nonlinear optimization problem. We present a linear approach which concentrates on time-dependent and discrete aspects. The nonlinearities are approximated by piece-wise linear functions using the concept of SOS constraints. We develop a branch-and-cut algorithm which has the potential to guarantee global optimality of the linearized problem where the nonlinearities are approximated within a given accuracy. We include an adequate handling of the SOS conditions and a separation algorithm for switching processes of compressors. A simulated annealing algorithm is included yielding feasible solutions. Our computational results show the success of our approach in this challenging field of gas network optimization.

关键词： mixed integer programming transient gas optimization piece-wise linear approximation SOS condition branch-and-cut

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Operational workforce planning for check-in counters at airports

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2010年第3期46卷 414-425页

作者： Stolletz, Raik Tech Univ Denmark Dept Engn Management DK-2800 Lyngby Denmark

This paper addresses operation models for workforce planning for check-in systems at airports. We characterize different tasks of the hierarchical workforce planning problem with time-dependent demand. A binary linear programming formulation is developed for the fortnightly tour scheduling problem with flexible employee contracts. This binary programming model is solved for optimality by CPLEX for real-world demand scenarios with different workforce sizes. The numerical study analyzes the impact of the degree of flexibility and economies of scale. The model formulation is extended to generate convenient tours with regard to employee preferences. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Airport operations management mixed integer programming Staff scheduling Tour scheduling

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Transmission Congestion Management through Optimal Distributed Generation's Sizing and Placement

Transmission Congestion Management through Optimal Distribut...

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International Conference on Environment and Electrical Engineering

作者： Mojtaba Khanabadi Meysam Doostizadeh Ahad Esmaeilian Mohsen Mohseninezhad University of Tehran

ISBN: (纸本)9781424487790

In both vertically integrated and restructured power systems, it is desired to transmit power to every parts of the network without any limits resulted from congestion and consequently avoiding inefficiency in generation dispatch. In this paper, in order to eliminate power system's congestion, distributed generation (DG) is employed. DG's have nonlinear impacts on the power system characteristics such as, the power transmitted between two locations of the network. Hence for identifying the impacts of DG on system variables, the problem of DG's sizing and placement is formulated as an AC optimal power flow (ACOPF) with binary variables and is solved by using mixed integer programming (MIP). In order to test the feasibility of mentioned method, the IEEE-14 bus systems has been used and also to study the impacts of DG's on this system, a number of system variables have been studied including: generation cost, congestion rent, locational marginal price (LMP), voltage profile and transmission losses.

关键词： Distributed generation DG Transmission congestion ACOPF mixed integer programming

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