检索结果-内蒙古大学图书馆

A Novel mixed integer programming Model With Precedence Relation-Based Decision Variables for Non-Cyclic Scheduling of Cluster Tools

引用

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 2893-2908页

作者： Ahn, Jeongsun Kim, Hyun-Jung Korea Adv Inst Sci & Technol Dept Ind & Syst Engn Daejeon 34141 South Korea

Cluster tools, which are extensively used in semiconductor and display manufacturing, offer the capability to perform multiple processing steps within a single tool. Many companies have recently been reducing wafer lot sizes due to diversified customer demands and circuit width reduction, resulting in more frequent transient and non-cyclic periods. We therefore present a novel mixed integer programming (MIP) model that can handle these non-cyclic scheduling problems of cluster tools. Our model is specifically designed to efficiently handle various wafer flows, accommodating both single- and dual-armed robots, while ensuring a shorter computation time, compared to the previous formulations. We first model cluster tools with a timed Petri net (TPN) and develop several precedence relations between transitions by analyzing the characteristics of the scheduling problems. These precedence relations are incorporated into a TPN by introducing additional places and arcs. This modification helps reduce the overall number of decision variables involved in the scheduling problem. We then develop an MIP model which specifies the precedence relations between transitions, as opposed to the position-based decision variables used in the previous studies. The proposed MIP model is capable of handling various flow scenarios encountered in cluster tools, including serial, parallel, concurrent, and re-entrant flows with time window constraints. Note to Practitioners-In response to the diverse demands of customers, the use of larger wafer sizes, and the need for smaller circuit widths, operating cluster tools in a cyclic manner has become increasingly challenging. Cyclic scheduling, where the robot repeats a fixed sequence while assuming identical wafers, is no longer viable in such scenarios. Unfortunately, previous research on cluster tool scheduling has predominantly focused on cyclic scheduling, failing to address the growing importance of non-cyclic scenarios. To address this gap, w

关键词： Non-cyclic scheduling cluster tool mixed integer programming precedence-based decision variables

来源：评论

学校读者我要写书评

暂无评论

A fix-propagate-repair heuristic for mixed integer programming

引用

MATHEMATICAL programming COMPUTATION 2025年第1期17卷 111-139页

作者： Salvagnin, Domenico Roberti, Roberto Fischetti, Matteo Univ Padua Dept Informat Engn DEI Padua Italy

We describe a diving heuristic framework based on constraint propagation for mixed integer linear programs. The proposed approach is an extension of the common fix-and-propagate scheme, with the addition of solution repairing after each step. The repair logic is loosely based on the WalkSAT strategy for boolean satisfiability. Different strategies for variable ranking and value selection, as well as other options, yield different diving heuristics. The overall method is relatively inexpensive, as it is basically LP-free: the full linear programming relaxation is solved only at the beginning (and only for the ranking strategies that make use of it), while additional, typically much smaller, LPs are only used to compute values for the continuous variables (if any), once at the bottom of a dive. While individual strategies are not very robust in finding feasible solutions on a heterogeneous testbed, a portfolio approach proved quite effective. In particular, it could consistently find feasible solutions in 189 out of 240 instances from the public MIPLIB 2017 benchmark testbed, in a matter of a few seconds of runtime. The framework has also been implemented inside the commercial MIP solver Xpress and shown to give a small performance improvement in time to optimality on a large internal heterogeneous testbed.

关键词： mixed integer programming Heuristics Solution repair Constraint propagation

来源：评论

学校读者我要写书评

暂无评论

A data-driven mixed integer programming approach for joint chance-constrained optimal power flow under uncertainty

引用

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2025年第2期16卷 1111-1127页

作者： Qin, James Ciyu Jiang, Rujun Mo, Huadong Dong, Daoyi Univ New South Wales Sch Engn & Technol Northcott Dr Canberra ACT 2612 Australia Fudan Univ Sch Data Sci Handan Rd Shanghai 20043 Peoples R China Australian Natl Univ Sch Engn CIICADA Lab Univ Ave Canberra ACT 2601 Australia

This paper introduces a novel mixed integer programming (MIP) reformulation for the joint chance-constrained optimal power flow problem under uncertain load and renewable energy generation. Unlike traditional models, our approach incorporates a comprehensive evaluation of system-wide risk without decomposing joint chance constraints into individual constraints, thus preventing overly conservative solutions and ensuring robust system security. A significant innovation in our method is the use of historical data to form a sample average approximation that directly informs the MIP model, bypassing the need for distributional assumptions to enhance solution robustness. Additionally, we implement a model improvement strategy to reduce the computational burden, making our method more scalable for large-scale power systems. Our approach is validated against benchmark systems, i.e., IEEE 14-, 57- and 118-bus systems, demonstrating superior performance in terms of cost-efficiency and robustness, with lower computational demand compared to existing methods.

关键词： Chance-constrained optimisation mixed integer programming Optimal power flow

来源：评论

学校读者我要写书评

暂无评论

Optimal control for HVAC system under uncertainty - a stochastic mixed integer programming mo del

引用

JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS 2025年

作者： Wang, Kung-Jeng Chen, Sheng-Hsuan Tseng, Shih-Hsien Wang, Kung-Min Cheng, Wen-Yu Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei Taiwan CECI Engn Consulting Inc Dept Mech Engn Taipei Taiwan

Manufacturing industries are significant consumers of energy, particularly in the realm of heating, ventilation, and air conditioning (HVAC) systems. Existing studies on HVAC systems tend to focus on optimizing individual components in isolation, leading to suboptimal outcomes due to partial optimization. In response, this study introduces an optimal control approach for HVAC systems in manufacturing industries, aiming to address dynamic cooling demands and variations in outdoor temperatures comprehensively. A stochastic mixed-integer programming model has been designed to optimize heating and cooling decisions within HVAC systems, with a primary focus on energy conservation. The study also examines the impact of various cooling demand patterns. The effectiveness of the proposed model is validated through its application to a panel manufacturing firm, demonstrating potential savings of up to 3.2% in total HVAC energy consumption.

关键词： Energy conservation mixed integer programming stochastic optimization heating, ventilation, and air conditioning (HVAC)

来源：评论

学校读者我要写书评

暂无评论

Bounds on Polarization Problems on Compact Sets via mixed integer programming

引用

DISCRETE & COMPUTATIONAL GEOMETRY 2025年第2期73卷 550-568页

作者： Rolfes, Jan Schueler, Robert Zimmermann, Marc Christian Friedrich Alexander Univ Erlangen Nurnberg Dept Data Sci Cauerstr 11 D-91058 Erlangen Germany KTH Royal Inst Technol Optimizat & Syst Theory Lindtstedtsvagen 25 S-11428 Stockholm Sweden Univ Rostock Inst Math Univ platz 1 D-18051 Rostock Germany Univ Cologne Abt Math Weyertal 86-90 D-50931 Cologne Germany

Finding point configurations, that yield the maximum polarization (Chebyshev constant) is gaining interest in the field of geometric optimization. In the present article, we study the problem of unconstrained maximum polarization on compact sets. In particular, we discuss necessary conditions for local optimality, such as that a locally optimal configuration is always contained in the convex hull of the respective darkest points. Building on this, we propose two sequences of mixed-integer linear programs in order to compute lower and upper bounds on the maximal polarization, where the lower bound is constructive. Moreover, we prove the convergence of these sequences towards the maximal polarization.

关键词： Maximal polarization Potentials mixed integer programming Geometric optimization

来源：评论

学校读者我要写书评

暂无评论

Application of mixed integer programming and simulated annealing algorithm in sustainable logistics network design

引用

JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2025年

作者： Wang, Nana Liaoning Univ Int Business & Econ Sch Liberal Educ 33 Shunle St Dalian City 116052 Liaoning Provin Peoples R China

This article integrates mixed integer programming and the simulated annealing algorithm to enhance both the economic efficiency and environmental sustainability of logistics networks. A multi-objective optimization model is first developed, incorporating economic costs, carbon emissions, and social service levels to address the diverse needs of stakeholders. A solution approach combining the precision of mixed integer programming with the global search capabilities of the simulated annealing algorithm is then proposed. This hybrid approach effectively overcomes the limitations of traditional optimization methods, particularly in managing complex constraints and large-scale problems. Through practical case studies, the proposed method demonstrated superior optimization performance. The average total cost after optimization was $52,444.61, outperforming solutions derived from using either mixed integer programming or simulated annealing alone. Furthermore, the service satisfaction rate exceeded 90%, indicating the model's effectiveness in balancing multiple objectives. The findings of this study not only offer a novel theoretical framework for logistics network design but also provide valuable support for enterprises striving to achieve sustainable development in their operations. The research highlights the potential to strike a harmonious balance between economic, environmental, and social responsibilities, paving the way for more sustainable and efficient logistics practices.

关键词： sustainable logistics network design mixed integer programming simulated annealing algorithm multi-objective optimization model environmental friendliness

来源：评论

学校读者我要写书评

暂无评论

mixed integer programming based maintenance scheduling for the Hunter Valley coal chain

引用

JOURNAL OF SCHEDULING 2013年第6期16卷 649-659页

作者： Boland, Natashia Kalinowski, Thomas Waterer, Hamish Zheng, Lanbo Univ Newcastle Sch Math & Phys Sci Callaghan NSW 2308 Australia

We consider the scheduling of the annual maintenance for the Hunter Valley Coal Chain. The coal chain is a system comprising load points, railway track and different types of terminal equipment, interacting in a complex way. A variety of maintenance tasks have to be performed on all parts of the infrastructure on a regular basis in order to assure the operation of the system as a whole. The main objective in the planning of these maintenance jobs is to maximize the total annual throughput. Based on a network flow model of the system, we propose a mixed integer programming formulation for this planning task. In order to deal with the resulting large scale model which cannot be solved directly by a general purpose solver, we propose two steps. The number of binary variables is reduced by choosing a representative subset of the variables of the original problem, and a rolling horizon approach enables the approximation of the long term (i.e. annual) problem by a sequence of shorter problems (for instance, monthly).

关键词： Maintenance scheduling Coal supply chain Capacity alignment Network flow mixed integer programming

来源：评论

学校读者我要写书评

暂无评论

mixed integer programming models for planning maintenance at offshore wind farms under uncertainty

引用

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2020年第0期112卷 180-202页

作者： Schrotenboer, Albert H. Ursavas, Evrim Vis, Iris F. A. Univ Groningen Fac Econ & Business Dept Operat Groningen Netherlands

We introduce the Stochastic Maintenance Fleet Transportation Problem for Offshore wind farms (SMFTPO), in which a maintenance provider determines an optimal, medium-term planning for maintaining multiple wind farms while controlling for uncertainty in the maintenance tasks and weather conditions. Since the maintenance provider is typically not the owner of a wind farm, it needs to adhere minimum service requirements that specify the required service. We consider three of such settings: (1) perform all maintenance tasks, (2) allow for a fraction of unscheduled tasks, and (3) incentivize to perform maintenance rather quickly. We provide a two-stage stochastic mixed integer programming model for the three SMFTPO settings, and solve it by means of Sample Average Approximation. In addition, we provide an overview of the, what we discovered, non-aligned modeling assumptions in the literature regarding operational decisions. By providing a series of special cases of the second-stage problem resembling the different modeling assumptions, we aim to establish a common consensus regarding the key modeling decisions to be taken in maintenance planning problems for offshore wind farms. We provide newly constructed, and publicly available, benchmark sets. We extensively compare the different SMFTPO settings and its special cases on those benchmark sets, and we show that the special case reformulations are very effective for solving the second-stage problems. In addition, we find that for particular cases, established modeling techniques result in overestimations and increased running times.

关键词： mixed integer programming Stochastic programming Offshore wind Transportation Service logistics Maintenance

来源：评论

学校读者我要写书评

暂无评论

mixed integer programming and multi-objective enhanced differential evolution algorithm for human-robot responsive collaborative disassembly in remanufacturing system

引用

ADVANCED ENGINEERING INFORMATICS 2024年 62卷

作者： Zhang, Zeqiang Liang, Wei Ji, Dan Zeng, Yanqing Zhang, Yu Li, Yan Zhu, Lixia Southwest Jiaotong Univ Sch Mech Engn Technol & Equipment Rail Transit Operat & Maintena Chengdu 610031 Peoples R China Tangshan Inst Tangshan 063000 Peoples R China Southwest Jiaotong Univ Chengdu 610031 Peoples R China Wenzhou Univ Sch Mech & Elect Engn Wenzhou 325035 Peoples R China

The recycling of waste products is essential for resource reuse. However, turning operation direction causes significant fatigue to operators handling end-of-life (EoL) products, consequently degrading the recycling efficiency. Accordingly, this study employs responsive collaboration robots to aid operators in turning the operation direction of disassembled products. To solve the human-robot responsive collaboration disassembly line balancing problem (HRRC-DLBP), a mixed integer programming (MIP) model is constructed, and a decoding mechanism is designed in this study. Additionally, a multi-objective enhanced differential evolution algorithm (MEDE) in which the decoding mechanism is incorporated is devised and applied to solve the HRRC-DLBP. The MEDE algorithm is validated by comparing its solution results with those of the MIP model. Finally, the MEDE is used to optimise the EoL printer case for the HRRC-DLBP and the disassembly line balancing problem in which the operation direction is turned by humans (H-DLBP). The optimisation results show that the recycling of EoL products is more efficient using the HRRC-DLBP than employing the H-DLBP.

关键词： Remanufacturing system Disassembly line balancing Human-robot responsive collaboration mixed integer programming Multi-objective enhanced differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

mixed integer programming models for job shop scheduling: A computational analysis

引用

COMPUTERS & OPERATIONS RESEARCH 2016年第Sep.期73卷 165-173页

作者： Ku, Wen-Yang Beck, J. Christopher Univ Toronto Dept Mech & Ind Engn 5 Kings Coll Rd Toronto ON M5S 3G8 Canada

In both industry and the research literature, mixed integer programming (MIP) is often the default approach for solving scheduling problems. In this paper we present and evaluate four MIP formulations for the classical job shop scheduling problem (JSP). While MIP formulations for the JSP have existed since the 1960s, it appears that comprehensive computational studies have not been performed since then. Due to substantial improvements in MIP technology in recent years, it is of interest to compare the standard JSP models using modern optimization software. We perform a fully crossed empirical study of four MIP models using CPLEX, GUROBI and SCIP, focusing on both the number of instances that can be proved optimal and the solution quality over time. Our results demonstrate that modern MIP solvers are able to prove optimality for moderate-sized problems very quickly. Comparing the four MIP models, the disjunctive formulation proposed by Manne performs best on both performance measures. We also investigate the performance of MIP with multi-threading and parameter tuning using CPLEX. Noticeable performance gain is observed when compared to the results using only single thread and default parameter settings. Our results serve as a snapshot of the performance of modern MIP solvers for an important, well-studied scheduling problem. Finally, the results of MW is compared to constraint programming (CP), another common approach for scheduling, and the best known complete algorithm to provide a broad view among different approaches. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Job shop scheduling mixed integer programming Constraint programming

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：