检索结果-内蒙古大学图书馆

A generalized disjunctive programming model for the static bike sharing rebalancing problem with demand intervals

OPTIMIZATION AND ENGINEERING 2025年 1-33页

作者： Ikonen, Teemu J. Heljanko, Keijo Harjunkoski, Iiro Aalto Univ Dept Chem & Met Engn Kemistintie 1 Espoo 02150 Finland Univ Helsinki Dept Comp Sci Pietari Kalmin Katu 5 Helsinki 00560 Finland Univ Helsinki Helsinki Inst Informat Technol HIIT Pietari Kalmin Katu 5 Helsinki 00560 Finland Hitachi Energy Res Havellandstr 10-14 D-68309 Mannheim Germany

Solving a static bike sharing rebalancing problem requires finding the minimum-cost route for rebalancing vehicles, subject to meeting the demand at the bike sharing stations of the system. In this work, we study the variant of the problem where the demand is specified by intervals, which adds flexibility to the routing of the rebalancing vehicles. We propose a generalized disjunctive programming (GDP) model to represent the problem and its reformulation into a mixed-integer linear programming (MILP) model. We use demand splitting to duplicate stations that require multiple visits. The model is designed for single-vehicle routing but can be used jointly with a clustering approach proposed in the literature for multi-vehicle routing. The model can solve to optimality 86.8% of benchmark instances with 70 stations within two hours of computing time. On test cases derived from real process data, the model is more than two orders of magnitude faster than the reference model in the literature.

关键词： Routing Bike sharing Combinatorial optimization Inventory generalized disjunctive programming

来源：评论

学校读者我要写书评

暂无评论

generalized disjunctive programming model for the multi-period production planning optimization: An application in a polyurethane foam manufacturing plant

引用

COMPUTERS & CHEMICAL ENGINEERING 2017年 103卷 69-80页

作者： Analia Rodriguez, Maria Marcelo Montagna, Jorge Vecchietti, Aldo Corsano, Gabriela Consejo Nacl Invest Cient & Tecn UNC PLAPIQUI IDTQ Av Velez Sarsfield 1611Ciudad UnivX5016GCA Cordoba Argentina Consejo Nacl Invest Cient & Tecn UTN INGAR Avellaneda 3657 RA-3000 Santa Fe Argentina

A generalized disjunctive programming (GDP) model for the optimal multi-period production planning and stock management is proposed in this work. The formulation is applied to a polyurethane foam manufacturing plant that comprises three stages: a first step that produces pieces with certain characteristics, a second process that involves the location of these pieces in a limited area and a third stage where pieces are stored in dedicated spaces. This article shows the GDP capabilities to provide a qualitative framework for representing the problem issues and their connections in a natural way, especially in a context where decisions integration is required. Due to the multi-period nature of the planning problem, a rolling horizon approach is suitable for solving it in reasonable computing time. It serves as a tool for analyzing the trade-offs among the different costs. Through the examples, the capabilities of the formulation and the proposed resolution method are highlighted. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： generalized disjunctive programming Production planning Stock Optimization Rolling horizon Mattress industry

来源：评论

学校读者我要写书评

暂无评论

Extensions to generalized disjunctive programming: hierarchical structures and first-order logic

引用

OPTIMIZATION AND ENGINEERING 2024年第2期25卷 605-+页

作者： Perez, Hector D. Grossmann, Ignacio E. Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

Optimization problems with discrete-continuous decisions are traditionally modeled in algebraic form via (non)linear mixed-integer programming. A more systematic approach to modeling such systems is to use generalized disjunctive programming (GDP), which extends the disjunctive programming paradigm proposed by Egon Balas to allow modeling systems from a logic-based level of abstraction that captures the fundamental rules governing such systems via algebraic constraints and logic. Although GDP provides a more general way of modeling systems, it warrants further generalization to encompass systems presenting a hierarchical structure. This work extends the GDP literature to address two major alternatives for modeling and solving systems with nested (hierarchical) disjunctions: explicit nested disjunctions and equivalent single-level disjunctions. We also provide theoretical proofs on the relaxation tightness of such alternatives, showing that explicitly modeling nested disjunctions is superior to the traditional approach discussed in literature for dealing with nested disjunctions.

关键词： generalized disjunctive programming Hierarchical systems Discrete-continuous optimization

来源：评论

学校读者我要写书评

暂无评论

The design of optimal mixtures from atom groups using generalized disjunctive programming

引用

COMPUTERS & CHEMICAL ENGINEERING 2018年 116卷 401-421页

作者： Jonuzaj, Suela Gupta, Aparana Adjiman, Claire S. Imperial Coll London Dept Chem Engn Ctr Proc Syst Engn London SW7 2AZ England Indian Inst Technol Delhi Dept Chem Engn Delhi India

A comprehensive computer-aided mixture/blend design methodology for formulating a general mixture design problem where the number, identity and composition of mixture constituents are optimized simultaneously is presented in this work. Within this approach, generalized disjunctive programming (GDP) is employed to model the discrete decisions (number and identities of mixture ingredients) in the problems. The identities of the components are determined by designing molecules from UNIFAC groups. The sequential design of pure compounds and blends, and the arbitrary pre-selection of possible mixture ingredients can thus be avoided, making it possible to consider large design spaces with a broad variety of molecules and mixtures. The proposed methodology is first applied to the design of solvents and solvent mixtures for maximising the solubility of ibuprofen, often sought in crystallization processes;next, antisolvents and antisolvent mixtures are generated for minimising the solubility of the drug in drowning out crystallization;and finally, solvent and solvent mixtures are designed for liquid-liquid extraction. The GDP problems are converted into mixed-integer form using the big-M approach. Integer cuts are included in the general models leading to lists of optimal solutions which often contain a combination of pure and mixed solvents. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： Mixture design generalized disjunctive programming UNIFAC groups Crystallization Antisolvent Liquid-liquid extraction

来源：评论

学校读者我要写书评

暂无评论

New algorithms for nonlinear generalized disjunctive programming

引用

COMPUTERS & CHEMICAL ENGINEERING 2000年第9-10期24卷 2125-2141页

作者： Lee, S Grossmann, IE Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

generalized disjunctive programming (GDP) has been introduced recently as an alternative model to MINLP for representing discrete/continuous optimization problems. The basic idea of GDP consists of representing discrete decisions in the continuous space with disjunctions, and constraints in the discrete space with logic propositions. In this paper, we describe a new convex nonlinear relaxation of the nonlinear GDP problem that relies on the use of the convex hull of each of the disjunctions involving nonlinear inequalities. The proposed nonlinear relaxation is used to reformulate the GDP problem as a tight MINLP problem, and for deriving a branch and bound method. Properties of these methods are given, and the relation of this method with the logic based outer-approximation method is established. Numerical results are presented for problems in jobshop scheduling synthesis of process networks, optimal positioning of new products and batch process design. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： generalized disjunctive programming branch and bound mixed-integer nonlinear programming nonlinear convex hull

来源：评论

学校读者我要写书评

暂无评论

Integration of modular process simulators under the generalized disjunctive programming framework for the structural flowsheet optimization

引用

COMPUTERS & CHEMICAL ENGINEERING 2014年 67卷 13-25页

作者： Navarro-Amoros, Miguel A. Ruiz-Femenia, Ruben Caballero, Jose A. Univ Alicante Dept Chem Engn E-03080 Alicante Spain

The optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied to the synthesis of a methanol plant where different alternatives are available for the streams, equipment and process conditions. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Process synthesis generalized disjunctive programming Modular simulators Logic based optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Process simulator-based optimization of biorefinery downstream processes under the generalized disjunctive programming framework

引用

COMPUTERS & CHEMICAL ENGINEERING 2016年 88卷 73-85页

作者： Corbetta, Michele Grossmann, Ignacio E. Manenti, Flavio Politecn Milan Dipartimento Chim Mat & Ingn Chim Giulio Natta Piazza Leonardo da Vinci 32 I-20133 Milan Italy Carnegie Mellon Univ Dept Chem Engn 5000 Forbes Ave Pittsburgh PA 15213 USA

Downstream processing of biofuels and bio-based chemicals represents a challenging problem for process synthesis and optimization, due to the intrinsic nonideal thermodynamics of the liquid mixtures derived from the (bio) chemical conversion of biomass. In this work, we propose a new interface between the process simulator PRO/II (SimSci, Schneider-Electric) and the optimization environment of GAMS for the structural and parameter optimization of this type of flowsheets with rigorous and detailed models. The optimization problem is formulated within the generalized disjunctive programming (GDP) framework and the solution of the reformulated MINLP problem is approached with a decomposition strategy based on the Outer-Approximation algorithm, where NLP subproblems are solved with the derivative free optimizer belonging to the BzzMath library, and MILP master problems are solved with CPLEX/GAMS. Several validation examples are proposed spanning from the economic optimization of two different distillation columns, the dewatering task of diluted bio-mixtures, up to the distillation sequencing with simultaneous mixed-integer design of each distillation column for a quaternary mixture in the presence of azeotropes. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： generalized disjunctive programming MINLP Downstream Process simulator Azeotropes Derivative free optimization

来源：评论

学校读者我要写书评

暂无评论

The Formulation of Optimal Mixtures with generalized disjunctive programming: A Solvent Design Case Study

引用

AICHE JOURNAL 2016年第5期62卷 1616-1633页

作者： Jonuzaj, Suela Akula, Paul T. Kleniati, Polyxeni-Margarita Adjiman, Claire S. Univ London Imperial Coll Sci Technol & Med Ctr Proc Syst Engn Dept Chem Engn South Kensington Campus London SW7 2AZ England W Virginia Univ Dept Chem Engn Morgantown WV 26506 USA Proc Syst Enterprise Ltd 26-28 Hammersmith Grove London W6 7HA England

Systematic approaches for the design of mixtures, based on a computer-aided mixture/blend design (CAM(b)D) framework, have the potential to deliver better products and processes. In most existing methodologies the number of mixture ingredients is fixed (usually a binary mixture) and the identity of at least one compound is chosen from a given set of candidate molecules. A novel CAM(b)D methodology is presented for formulating the general mixture design problem where the number, identity and composition of mixture constituents are optimized simultaneously. To this end, generalized disjunctive programming is integrated into the CAM(b)D framework to formulate the discrete choices. This generic methodology is applied to a case study to find an optimal solvent mixture that maximizes the solubility of ibuprofen. The best performance in this case study is obtained with a solvent mixture, showing the benefit of using mixtures instead of pure solvents to;attain enhanced behavior. (C) 2016 The Authors AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers

关键词： computer-aided mixture design generalized disjunctive programming optimal mixture design ibuprofen solubility

来源：评论

学校读者我要写书评

暂无评论

Global optimization of nonlinear generalized disjunctive programming with bilinear equality constraints: applications to process networks

引用

COMPUTERS & CHEMICAL ENGINEERING 2003年第11期27卷 1557-1575页

作者： Lee, S Grossmann, IE Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

A global optimization method is proposed for the solution of nonconvex generalized disjunctive programming problems that have bilinear equality constraints in terms of flows, compositions and split fractions. Tight convex under/over estimators are introduced for the relaxation of nonconvex constraints to construct the lower bound problem. Discrete choices for process networks are expressed as disjunctions, which are relaxed by a convex hull formulation. The relaxed convex NLP problem is solved with a two-level branch and bound algorithm proposed by Lee and Grossmann (Comput. Chem. Eng. 25 (2001) 1675), which branches on the discrete variables at the first level and the continuous variables on the second level. This global optimization algorithm is guaranteed to find an F-optimal solution in a finite number of steps. Applications are presented in pooling problems, wastewater network problems, and water usage network problems. (C) 2003 Elsevier Science Ltd. All rights reserved.

关键词： global optimization generalized disjunctive programming nonconvex equality constraints convex hull relaxation

来源：评论

学校读者我要写书评

暂无评论

A hierarchy of relaxations for nonlinear convex generalized disjunctive programming

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2012年第1期218卷 38-47页

作者： Ruiz, Juan P. Grossmann, Ignacio E. Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

We propose a framework to generate alternative mixed-integer nonlinear programming formulations for disjunctive convex programs that lead to stronger relaxations. We extend the concept of "basic steps" defined for disjunctive linear programs to the nonlinear case. A basic step is an operation that takes a disjunctive set to another with fewer number of conjuncts. We show that the strength of the relaxations increases as the number of conjuncts decreases, leading to a hierarchy of relaxations. We prove that the tightest of these relaxations, allows in theory the solution of the disjunctive convex program as a nonlinear programming problem. We present a methodology to guide the generation of strong relaxations without incurring an exponential increase of the size of the reformulated mixed-integer program. Finally, we apply the theory developed to improve the computational efficiency of solution methods for nonlinear convex generalized disjunctive programs (GDP). This methodology is validated through a set of numerical examples. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Combinatorial optimization Convex programming disjunctive programming generalized disjunctive programming Tight relaxations

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：