检索结果-内蒙古大学图书馆

MINLP-based hybrid strategy for operating mode selection of TES-backed-up refrigeration systems

INTERNATIONAL JOURNAL OF ROBUST AND nonlinear CONTROL 2020年第15期30卷 6091-6111页

作者： Bejarano, Guillermo Rodriguez, David Lemos, Joao M. Varga, Manuel Ortega, Manuel G. Univ Loyola Andalucia Dept Ingn Escuela Tecn Super Ingn Campus Palmas Altas Seville 41014 Spain Univ Seville Dept Ingn Sistemas & Automat Escuela Tecn Super Ingn Seville Spain Univ Lisbon Inst Super Tecn INESC ID Lisbon Portugal

This brief deals with the satisfaction of the daily cooling demand by a hybrid system that consists of a vapor-compression refrigeration cycle and a thermal energy storage (TES) unit, based on phase change materials. The addition of the TES tank to the original refrigeration plant allows to schedule the cooling production regardless of the instantaneous demand, given that the TES tank can store cold energy and release it whenever deemed appropriate. The scheduling problem is posed as an optimization problem based on mixed-integer nonlinear programming (MINLP) since it includes both discrete and continuous variables. The latter corresponds to the references on the main cooling powers involved in the problem (cooling production at the evaporator and TES charging/discharging), whereas the discrete variables define the operating mode scheduling. Therefore, in addition to the hybrid features of the physical plant, a hybrid optimal control strategy is also proposed. A receding horizon approach is applied, similar to model predictive control (MPC) strategies, while economic criteria are imposed in the objective function, as well as feasibility issues. The TES state estimation is also addressed since its instantaneous charge ratio is not measurable. The proposed strategy is applied in simulation to a challenging cooling demand profile, and the main advantages of the MINLP-based strategy over a nonlinear MPC-based scheduling strategy previously developed are highlighted, regarding operating cost, ease of tuning, and ability to adapt to cooling demand variations.

关键词： mixed-integer nonlinear programming phase change materials refrigeration system scheduling thermal energy storage

来源：评论

学校读者我要写书评

暂无评论

Solving reliability redundancy allocation problems using an artificial bee colony algorithm

引用

COMPUTERS & OPERATIONS RESEARCH 2011年第11期38卷 1465-1473页

作者： Yeh, Wei-Chang Hsieh, Tsung-Jung Natl Tsing Hua Univ Dept Ind Engn & Engn Management Hsinchu 30013 Taiwan

This paper proposed a penalty guided artificial bee colony algorithm (ABC) to solve the reliability redundancy allocation problem (RAP). The redundancy allocation problem involves setting reliability objectives for components or subsystems in order to meet the resource consumption constraint, e.g. the total cost. RAP has been an active area of research for the past four decades. The difficulty that one is confronted with the RAP is the maintenance of feasibility with respect to three nonlinear constraints, namely, cost, weight and volume related constraints. In this paper nonlinearly mixed-integer reliability design problems are investigated where both the number of redundancy components and the corresponding component reliability in each subsystem are to be decided simultaneously so as to maximize the reliability of the system. The reliability design problems have been studied in the literature for decades, usually using mathematical programming or heuristic optimization approaches. To the best of our knowledge the ABC algorithm can search over promising feasible and infeasible regions to find the feasible optimal/near-optimal solution effectively and efficiently;numerical examples indicate that the proposed approach performs well with the reliability redundant allocation design problems considered in this paper and computational results compare favorably with previously-developed algorithms in the literature. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Reliability design Redundancy allocation problem Artificial bee colony algorithm mixed-integer nonlinear programming

来源：评论

学校读者我要写书评

暂无评论

Solving AC Optimal Power Flow with Discrete Decisions to Global Optimality

引用

INFORMS JOURNAL ON COMPUTING 2023年第2期35卷 458-474页

作者： Aigner, Kevin-Martin Burlacu, Robert Liers, Frauke Martin, Alexander Friedrich Alexander Univ Erlangen Nurnberg Discrete Optimizat D-91058 Erlangen Germany Energie Campus Nurnberg D-90429 Nurnberg Germany Fraunhofer Inst Integrated Circuits D-90411 Nurnberg Germany

We present a solution framework for general alternating current optimal power flow (AC OPF) problems that include discrete decisions. The latter occur, for instance, in the context of the curtailment of renewables or the switching of power-generation units and transmission lines. Our approach delivers globally optimal solutions and is provably convergent. We model AC OPF problems with discrete decisions as mixed-integer non-linear programs (MINLPs). The solution method starts from a known framework that uses piecewise linear relaxations. These relaxations are modeled as mixed-integer linear pro-grams and adaptively refined until some termination criterion is fulfilled. In this work, we extend and complement this approach by problem-specific as well as very general algorith-mic enhancements. In particular, these are mixed-integer second order cone programs as well as primal and dual cutting planes. For example, objective and no-good cuts help to compute good feasible solutions in which outer approximation constraints tighten the relaxations. We present extensive numerical results for various AC OPF problems in which discrete decisions play a major role. Even for hard instances with a large proportion of dis-crete decisions, the method is able to generate high-quality solutions efficiently. Further-more, we compare our approach with state-of-the-art MINLP solvers. Our method outperforms all other algorithms.

关键词： AC optimal power flow mixed-integer nonlinear programming discrete decisions second order cone programming piecewise linear relaxation generator switching transmission line switching curtailment of renewables

来源：评论

学校读者我要写书评

暂无评论

Optimising the configuration of food supply chains

引用

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2021年第12期59卷 3722-3746页

作者： Li, Haitao Li, De Jiang, Dali Univ Missouri Coll Business Adm Supply Chain & Analyt Dept St Louis MO 63121 USA Army Logist Univ PLA Dept Mil Logist Chongqing Peoples R China

We study the food supply chain configuration problem (FSCCP) to optimise the tactical-level mode selection and inventory positioning decisions for a general multi-echelon food supply chain. A mixed-integer nonlinear programming (MINLP) model is developed for the FSCCP, with new building blocks to address the perishability issue in terms of both food loss and quality deterioration. Our model minimises the system-wide total supply chain costs and balances multiple supply chain performance metrics: cost, time and quality. Computational studies show that the optimal FSCCP solutions significantly outperform two heuristic solutions that focus solely on cost or quality. Additional insights are obtained on the impacts of key input parameters on the optimal configuration and performance metrics.

关键词： supply chain configuration food supply chain perishability inventory positioning safety stock placement mixed-integer nonlinear programming

来源：评论

学校读者我要写书评

暂无评论

mixed-integer nonlinear programs featuring "on/off" constraints

引用

COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2012年第2期52卷 537-558页

作者： Hijazi, Hassan Bonami, Pierre Cornuejols, Gerard Ouorou, Adam Ecole Polytech LIX F-91128 Palaiseau France Aix Marseille Univ CNRS LIF Marseille France Carnegie Mellon Univ Tepper Sch Business Pittsburgh PA 15213 USA Orange Labs R&D CORE TPN F-92794 Issy Les Moulineaux 9 France

In this paper, we study MINLPs featuring "on/off" constraints. An "on/off" constraint is a constraint f(x)a parts per thousand currency sign0 that is activated whenever a corresponding 0-1 variable is equal to 1. Our main result is an explicit characterization of the convex hull of the feasible region when the MINLP consists of simple bounds on the variables and one "on/off" constraint defined by an isotone function f. When extended to general convex MINLPs, we show that this result yields tight lower bounds compared to classical formulations. This allows us to introduce new models for the delay-constrained routing problem in telecommunications. Numerical results show gains in computing time of up to one order of magnitude compared to state-of-the-art approaches.

关键词： mixed-integer nonlinear programming "on/off" constraints Disjunctive constraints Convex programming Delay-constrained routing problems

来源：评论

学校读者我要写书评

暂无评论

Undercover: a primal MINLP heuristic exploring a largest sub-MIP

引用

MATHEMATICAL programming 2014年第1-2期144卷 315-346页

作者： Berthold, Timo Gleixner, Ambros M. Zuse Inst Berlin Dept Optimizat D-14195 Berlin Germany

We present Undercover, a primal heuristic for nonconvex mixed-integer nonlinear programs (MINLPs) that explores a mixed-integer linear subproblem (sub-MIP) of a given MINLP. We solve a vertex covering problem to identify a smallest set of variables to fix, a so-called cover, such that each constraint is linearized. Subsequently, these variables are fixed to values obtained from a reference point, e.g., an optimal solution of a linear relaxation. Each feasible solution of the sub-MIP corresponds to a feasible solution of the original problem. We apply domain propagation to try to avoid infeasibilities, and conflict analysis to learn additional constraints from infeasibilities that are nonetheless encountered. We present computational results on a test set of mixed-integer quadratically constrained programs (MIQCPs) and MINLPs. It turns out that the majority of these instances allows for small covers. Although general in nature, we show that the heuristic is most successful on MIQCPs. It nicely complements existing root-node heuristics in different state-of-the-art solvers and helps to significantly improve the overall performance of the MINLP solver SCIP.

关键词： Primal heuristic mixed-integer nonlinear programming Large neighborhood search mixed-integer quadratically constrained programming Nonconvex optimization

来源：评论

学校读者我要写书评

暂无评论

Maximizing the storage capacity of gas networks: a global MINLP approach

引用

OPTIMIZATION AND ENGINEERING 2019年第2期20卷 543-573页

作者： Burlacu, Robert Egger, Herbert Gross, Martin Martin, Alexander Pfetsch, Marc E. Schewe, Lars Sirvent, Mathias Skutella, Martin Friedrich Alexander Univ Erlangen Nurnberg FAU Discrete Optimizat Cauerstr 11 D-91058 Erlangen Germany Tech Univ Darmstadt Res Grp Numer & Sci Comp Dolivostr 15 D-64293 Darmstadt Germany Rhein Westfal TH Aachen Chair Management Sci Kackertstr 7 D-52072 Aachen Germany Tech Univ Darmstadt Res Grp Optimizat Dolivostr 15 D-64293 Darmstadt Germany Tech Univ Berlin Fac Math & Nat Sci 2 Str 17 Juni 136 D-10623 Berlin Germany

In this paper, we study the transient optimization of gas networks, focusing in particular on maximizing the storage capacity of the network. We include nonlinear gas physics and active elements such as valves and compressors, which due to their switching lead to discrete decisions. The former is described by a model derived from the Euler equations that is given by a coupled system of nonlinear parabolic partial differential equations (PDEs). We tackle the resulting mathematical optimization problem by a first-discretize-then-optimize approach. To this end, we introduce a new discretization of the underlying system of parabolic PDEs and prove well-posedness for the resulting nonlinear discretized system. Endowed with this discretization, we model the problem of maximizing the storage capacity as a non-convex mixed-integer nonlinear problem (MINLP). For the numerical solution of the MINLP, we algorithmically extend a well-known relaxation approach that has already been used very successfully in the field of stationary gas network optimization. This method allows us to solve the problem to global optimality by iteratively solving a series of mixed-integer problems. Finally, we present two case studies that illustrate the applicability of our approach.

关键词： mixed-integer nonlinear programming Transient gas transport optimization Storage capacity maximization Power-to-gas First-discretize-then-optimize

来源：评论

学校读者我要写书评

暂无评论

Operational strategy and planning for raw natural gas refining complexes: Process modeling and global optimization

引用

AICHE JOURNAL 2017年第2期63卷 652-668页

作者： Zhang, Bing J. Chen, Qing L. Li, Jie Floudas, Christodoulos A. Sun Yat Sen Univ Sch Chem Engn & Technol Guangdong Engn Technol Res Ctr Petrochem Energy C Key Lab Low Carbon Chem & Energy Conservat Guangd 135 Xingang West Rd Guangzhou 510275 Guangdong Peoples R China Texas A&M Univ Artie McFerrin Dept Chem Engn 3122 TAMU College Stn TX 77843 USA Texas A&M Univ Texas A&M Energy Inst 3372 TAMU College Stn TX 77843 USA Univ Manchester Sch Chem Engn & Analyt Sci Manchester M13 9PL Lancs England

Optimal operational strategy and planning of a raw natural gas refining complex (RNGRC) is very challenging since it involves highly nonlinear processes, complex thermodynamics, blending, and utility systems. In this article, we first propose a superstructure integrating a utility system for the RNGRC, involving multiple gas feedstocks, and different product specifications. Then, we develop a large-scale nonconvex mixed-integer nonlinear programming (MINLP) optimization model. The model incorporates rigorous process models for input and output relations based on fundamentals of thermodynamics and unit operations and accurate models for utility systems. To reduce the noncovex items in the proposed MINLP model, equivalent reformulation techniques are introduced. Finally, the reformulated nonconvex MINLP model is solved to global optimality using state of the art deterministic global optimization approaches. The computational results demonstrate that a significant profit increase is achieved using the proposed approach compared to that from the real operation. (c) 2016 American Institute of Chemical Engineers AIChE J, 63: 652-668, 2017

关键词： natural gas operational planning mixed-integer nonlinear programming enterprise-wide optimization global optimization

来源：评论

学校读者我要写书评

暂无评论

Generalized orienteering problem with resource dependent rewards

引用

NAVAL RESEARCH LOGISTICS 2013年第4期60卷 294-312页

作者： Pietz, Jesse Royset, Johannes O. USN Dept Operat Res Postgrad Sch Monterey CA USA

We introduce a generalized orienteering problem (OP) where, as usual, a vehicle is routed from a prescribed start node, through a directed network, to a prescribed destination node, collecting rewards at each node visited, to maximize the total reward along the path. In our generalization, transit on arcs in the network and reward collection at nodes both consume a variable amount of the same limited resource. We exploit this resource trade-off through a specialized branch-and-bound algorithm that relies on partial path relaxation problems that often yield tight bounds and lead to substantial pruning in the enumeration tree. We present the smuggler search problem (SSP) as an important real-world application of our generalized OP. Numerical results show that our algorithm applied to the SSP outperforms standard mixed-integer nonlinear programming solvers for moderate to large problem instances. We demonstrate model enhancements that allow practitioners to represent realistic search planning scenarios by accounting for multiple heterogeneous searchers and complex smuggler motion. (c) 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013

关键词： orienteering problem military operations research search and surveillance route planning mixed-integer nonlinear programming

来源：评论

学校读者我要写书评

暂无评论

The multi-floor cross-dock door assignment problem: Rising challenges for the new trend in logistics industry

引用

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2019年 132卷 30-47页

作者： Wang, Haibo Alidaee, Bahram Texas A&M Int Univ AR Sanchez Sch Business Laredo TX 78041 USA Univ Mississippi Sch Business Adm University MS 38677 USA

This paper is concerned with the multi-floor, cross-dock door assignment problem (MCDAP) to minimize the total material handling costs. We present a novel mixed-integer nonlinear programming model and a classic linearization form for the MCDAP. We use a combination of multi-start, genetic random-key, and very-large-scale neighborhood search (VLSN) as the diversification strategies for the solution perturbation method embedded within the critical event Tabu search to solve MCDAP. We will test the proposed algorithms on a set of 60 very-large sized instances with 150-300 loading doors, and 100-300 unloading doors that raise size of cost matrix up to 90,000 by 90,000.

关键词： Cross-dock door assignment Multi-floor warehouse mixed-integer nonlinear programming Tabu Search Genetic random-key Very-large-scale neighborhood search

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：