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MINLP based retrieval of generalized cases

7th European Conference on Case-Based Reasoning

作者： Tartakovski, A Schaaf, M Maximini, R Bergmann, R Univ Trier Dept Business Informat Syst 2 D-54286 Trier Germany Univ Hildesheim Inst Math & Appl Comp Sci Data & Knowledge Management Grp D-31113 Hildesheim Germany

ISBN: (纸本)3540228829

The concept of generalized cases has been proven useful when searching for configurable and flexible products, for instance, reusable components in the area of electronic design automation. This paper addresses the similarity assessment and retrieval problem for case bases consisting of traditional and generalized cases. While approaches presented earlier were restricted to continuous domains, this paper addresses generalized cases defined over mixed, continuous and discrete, domains. It extends the view on the similarity assessment as a nonlinear optimization problem (NLP) towards a mixed integer nonlinear optimization problem (MINLP), which is an actual research topic in mathematical optimization. This is an important step because most real world applications require mixed domains for the case description. Furthermore, we introduce two optimization-based retrieval methods that operate on a previously created index structure, which restricts the retrieval response time significantly.

关键词： generalized cases mixed integer nonlinear programming kd-trees

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On the boundary of tractability for nonlinear discrete optimization 8

On the boundary of tractability for nonlinear discrete optim...

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8th Cologne-Twente Workshop on Graphs and Combinatorial Optimization, CTW 2009

作者： Lee, Jon IBM TJ Watson Research Center PO Box 218 Yorktown HeightsNY10598 United States

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Modeling and Multi-objective Optimization of Refinery Hydrogen Network

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Chinese Journal of Chemical Engineering 2011年第6期19卷 990-998页

作者：焦云强苏宏业廖祖维侯卫锋 State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou 310027 China State Key Laboratory of Chemical Engineering Department of Chemical and Biological Engineering Zhejiang University Hangzhou 310027 China Zhejiang ＂Supcon Software Co. Ltd. Hangzhou 310053 China

The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming （MINLP）. A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.

关键词： refinery multi-objective optimization hydrogen network mixed integer nonlinear programming

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Simulated Annealing Approach to the Optimal Synthesis of Distillation Column with Intermediate Heat Exchangers

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Chinese Journal of Chemical Engineering 2008年第1期16卷 30-35页

作者：安维中于凤娟董凤蕾胡仰栋 Department of Chemical Engineering Ocean University of China Qingdao 266100 China

This article presents a simulated annealing-based approach to the optimal synthesis of distillation column considering intermediate heat exchangers arrangements. T-he number of intermediate condensers and/or intermediate reboilers, the placement locations, *** pressure of column, and the heat duties of intermediate heat exchangers are treated as optimization variables. A novel coding procedure making use of an integer number series is proposed to represent and manipulate the structure of system and a stage-to-stage method is used for column design and cost calculation. With the representation procedure, the synthesis problem is formulated as a mixed integer nonlinear programming （MINLP） problem, which can then be solved with an improved simulated annealing algorithm. Two examples are illustrated to show the effectiveness of the suggested approach.

关键词： distillation intermediate heat exchanger synthesis mixed integer nonlinear programming simulated annealing

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Realigning the U. S. Navy Recruiting Command

Realigning the U. S. Navy Recruiting Command

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作者： Schwartz, Garry S. Naval Postgraduate School

学位级别：硕士

This thesis addresses two problems in aligning the recruiting structure for Navy Recruiting Command. The first problem involves two decisions affecting recruiting stations within a single recruiting district: which stations should remain open and how many recruiters should be assigned to each open station? The second problem is to decide how many recruiters and stations each district should have. The first problem is formulated as a nonlinear mixed integer programming problem. To obtain a solution with readily available software, the problem is decomposed into four subproblems that are solved sequentially. This decomposition approach is empirically shown to yield near optimal solutions for problems of varied sizes. The second problem is formulated as a nonlinear resource allocation problem in which the objective function is not expressible in closed form. To efficiently solve this problem, the function is approximated in a piecewise linear fashion using the results from the first problem. To illustrate the applications of these optimization models, solutions were obtained for Navy Recruiting District Boston and Navy Recruiting Area 1, which consists of Albany, Boston, Buffalo. New York, Harrisburg, Philadelphia, Pittsburgh and New Jersey districts.

关键词： mixed integer nonlinear programming Facility Location Piecewise Approximating Large Mathematical Models Decomposition of mixed Intever nonlinear Problems. Resource Allocation GAMS

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Optimization for Design and Operation of Natural Gas Transmission Networks

Optimization for Design and Operation of Natural Gas Transmi...

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作者： Dilaveroglu, Sebnem 1986- Texas A&M University

This study addresses the problem of designing a new natural gas transmission network or expanding an existing network while minimizing the total investment and operating costs. A substantial reduction in costs can be obtained by effectively designing and operating the network. A well-designed network helps natural gas companies minimize the costs while increasing the customer service level. The aim of the study is to determine the optimum installation scheduling and locations of new pipelines and compressor stations. On an existing network, the model also optimizes the total flow through pipelines that satisfy demand to determine the best purchase amount of gas. A mixed integer nonlinear programming model for steady-state natural gas transmission problem on tree-structured network is introduced. The problem is a multi-period model, so changes in the network over a planning horizon can be observed and decisions can be made accordingly in advance. The problem is modeled and solved with easily accessible modeling and solving tools in order to help decision makers to make appropriate decisions in a short time. Various test instances are generated, including problems with different sizes, period lengths and cost parameters, to evaluate the performance and reliability of the model. Test results revealed that the proposed model helps to determine the optimum number of periods in a planning horizon and the crucial cost parameters that affect the network structure the most.

关键词： mixed integer nonlinear programming Network design Natural gas Thesis

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Reactive Power Planning for Regional Power Grids Based on Active and Reactive Power Adjustments of DGs

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ENERGIES 2018年第6期11卷 1606-1606页

作者： Shen, Yangwu Shen, Feifan Chen, Yaling Liang, Liqing Zhang, Bin Ke, Deping Sate Grid Hunan Elect Power Corp Res Inst Changsha 410007 Hunan Peoples R China Tech Univ Denmark Dept Elect Engn DK-2008 Copenhagen Denmark Hunan Univ Chinese Med Sch Humanities & Management Changsha 410208 Hunan Peoples R China Wuhan Univ Dept Elect Engn Wuhan 430000 Hubei Peoples R China

To deal with extreme overvoltage scenarios with small probabilities in regional power grids, the traditional reactive power planning model requires a huge VAR compensator investment. Obviously, such a decision that makes a large investment to cope with a small probability event is not economic. Therefore, based on the scenario analysis of power outputs of distributed generations and load consumption, a novel reactive power planning model considering the active and reactive power adjustments of distributed generations is proposed to derive the optimal allocation of VAR compensators and ensure bus voltages within an acceptable range under extreme overvoltage scenarios. The objective of the proposed reactive power planning model is to minimize the VAR compensator investment cost and active power adjustment cost of distributed generations. Moreover, since the proposed reactive power planning model is formulated as a mixed-integer nonlinear programming problem, a primal-dual interior point method-based particle swarm optimization algorithm is developed to effectively solve the proposed model. Simulation results were conducted with the modified IEEE 30-bus system to verify the effectiveness of the proposed reactive power planning model.

关键词： reactive power planning distributed generation active power adjustment mixed integer nonlinear programming

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Optimal durations of Weibull reliability tests based on failure counts

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 156卷 107247-107247页

作者： Fernandez, Arturo J. Univ La Laguna Dept Matemat Estadist & Invest Operat Tenerife 38071 Canary Islands Spain

In industry, the durations of reliability experiments are usually fixed in advanced, which could lead to suboptimal results. A constrained optimization problem is stated in order to determine the best inspection time for reliability testing. The decision criterion is based on Weibull failure counts, whereas the constraints are related to the reliability and risk levels imposed by the producer and the consumer. The optimal reliability sampling plan provides the best strategy to determine the acceptability of lots and production processes. Minimum-cost inspection times, as well as the required number of test units and the maximum number of failures allowed, are derived by solving mixed integer nonlinear programming problems. An approximation of the minimum feasible acceptance number is first provided in closed-form. An efficient step-by-step procedure is then proposed in order to find the optimal reliability test plan for lot sentencing. In most cases, only a few iterations are needed to reach the optimal solution. For illustrative purposes, the suggested methodology is applied to the manufacturing of turbine engine combustors, systems of components and lawn mower motors.

关键词： Reliability Lot sampling inspection Constrained optimization mixed integer nonlinear programming Weibull distribution

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Minimal mass design of active tensegrity structures

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ENGINEERING STRUCTURES 2021年 234卷 111965-111965页

作者： Wang, Yafeng Xu, Xian Luo, Yaozhi Zhejiang Univ Coll Civil Engn & Architecture 866 Yuhangtang Rd Hangzhou 310058 Zhejiang Peoples R China Swiss Fed Inst Technol EPFL Sch Architecture Civil & Environm Engn ENAC Appl Comp & Mech Lab IMAC CH-1015 Lausanne Switzerland

Tensegrity structures have been widely utilized as lightweight structures due to their high stiffness-to-mass and strength-to-mass ratios. Minimal mass design of tensegrity structures subject to external loads and specific constraints (e.g., member yielding and buckling) has been intensively studied. However, all the existing studies focus on passive tensegrity structures, i.e., the structural members cannot change their lengths actively and the structure has to passively resist external loads. An active tensegrity structure equipped with actuators can actively adapt its internal forces and nodal positions and thus can actively resist external loads. Therefore, it is expected that active tensegrity structures use less material compared to passive tensegrity structures thus leading to a smaller mass. Due to the integration of the active control system, the design of active tensegrity structures is different from passive tensegrity structures. This study proposes a general approach for the design of minimal mass active tensegrity structures based on a mixed integer programming scheme, in which the member crosssectional areas, prestress, actuator layout and control strategies (i.e., actuator length changes) are designed simultaneously. The member cross-sectional areas, prestress level, and actuator control strategies are treated as continuous variables and the actuator layout is treated as a binary variable. The equilibrium condition, member yielding, cable slackness, strut buckling, and the limitations on the nodal displacements as well as other practical requirements are formulated as constraints. Three typical active tensegrity structures are designed through the proposed approach and the results are benchmarked with the equivalent minimal mass passive designs. It is illustrated that the active designs can significantly decrease the material consumption compared with the equivalent passive designs thus leading to more lightweight tensegrity structures.

关键词： Active tensegrity structure Minimal mass Lightweight structure Semi-definite programming mixed integer nonlinear programming

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Matheuristics vs. metaheuristics for joint lot-sizing and dynamic pricing problem with nonlinear demands

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COMPUTERS & OPERATIONS RESEARCH 2024年 163卷

作者： Terzi, Mourad Ouazene, Yassine Yalaoui, Alice Yalaoui, Farouk Univ Technol Troyes Comp Sci & Digital Soc Lab 12 Rue Marie Curie F-10004 Troyes France Univ Technol Troyes Chaire Connected Innovat 12 Rue Marie CurieCS 42060 F-10004 Troyes CS France Univ Technol Troyes Comp Sci & Digital Soc Lab LIST3N 12 rue Marie Curie F- 10004 Troyes France

This paper considers a joint dynamic pricing and production planning decisions problem for a profit-maximizing firm that produces and sells multiple products. The objective is to develop a coordinated decision approach for multi-product pricing and lot sizing decisions for a manufacturer considering a limited production capacity. The demand for each product is assumed to be iso-elastic and integrates the complementarity and the substitution effects between the products. First, the problem is formulated as a non-convex mixed integer nonlinear programming model (MINLP) incorporating capacity constraints, setup costs, and nonlinear demand functions. Then, since the model is nonlinear and non-convex, a set of approximate approaches based on the Genetic algorithm, Late Acceptance Hill Climbing and Simulated Annealing methods are designed to solve this problem. Based on this study, the performances of two variants of approximate methods: matheuristics and metaheuristics are discussed and analyzed. The extensive experimental study, performed on real-world inspired instances, shows that matheuristic methods with setup-variables encoding scheme outperform the rest of the methods. The research outcomes show that coordinating a decision-making process by optimizing both prices and production plans simultaneously can result in significant profit for a company. However, one must consider the joint effect of the parameters of the demand function as well as the impact of the production capacity. This comprehensive understanding enables the company to avoid excessive investments in less lucrative products with lower sales potential, thereby ensuring resource allocation aligns with profitability and market demand.

关键词： Dynamic pricing Lot-sizing Metaheuristics Matheuristics nonlinear demand model mixed integer nonlinear programming

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