检索结果-内蒙古大学图书馆

Finding the Nondominated Set and Efficient integer Vectors for a Class of Three-Objective mixed-integer linear programs

引用

MANAGEMENT SCIENCE 2023年第10期69卷 6001-6020页

作者： Ceyhan, Gokhan Koksalan, Murat Lokman, Banu Middle East Tech Univ Ind Engn TR-06800 Ankara Turkiye Univ Michigan Ross Sch Business Ann Arbor MI 48109 USA Univ Portsmouth Ctr Operat Res & Logist Sch Org Syst & People Portsmouth PO1 3DE Hants England

We consider a class of three-objective mixed-integer linear programs (MILPs) where at least one of the objective functions takes only discrete values. These problems commonly occur in MILPs where one or more of the three objective functions contain only integer decision variables. In such problems, the nondominated set consists of the union of nondominated edges and individual nondominated points. The nondominated edges can provide valuable insights on the trade-offs between the two continuous objectives at different levels of the discrete-valued objective. We develop an objective-space search algorithm that keeps partitioning the search space by progressively creating cones in the two-dimensional feasible space of the two continuous objectives for relevant values of the discrete-valued objective. The algorithm generates the nondominated points or edges in the nonincreasing order of the feasible values of the selected discrete-valued objective. Additionally, the algorithm uncovers all efficient integer variable vectors, including different vectors that lead to the same nondominated points or edges. We apply the algorithm to the day-ahead electricity market clearing problem.

关键词： multiobjective mixed-integer linear program objective-space search algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal Assignment and Scheduling of Cranes in Slab Yard for Iron and Steel Production Enterprises

引用

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 7349-7360页

作者： Wang, Xu Zhou, Mengchu Zhao, Qiuhong Liu, Shixin Guo, Xiwang Qi, Liang Albeshri, Aiiad Shenyang Univ Chem Technol Sch Comp Sci & Technol Shenyang 110142 Peoples R China Macau Univ Sci & Technol Macao Inst Syst Engn Macau 999078 Peoples R China New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA Beihang Univ Sch Econ & Management Beijing 100191 Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China Liaoning Shihua Univ Coll Comp & Commun Engn Fushun 113001 Peoples R China Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266590 Peoples R China King Abdulaziz Univ Dept Comp Sci Jeddah 21481 Saudi Arabia

Slab yards serve as temporary slab storage between a continuous casting stage and a rolling stage. Considering non-crossing and safe clearance constraints of slab yard cranes, this work studies a multi-crane assignment and scheduling problem in the slab yard. An mixed-integer linear programming (MILP) is formulated to minimize the slab completion time. Due to its NP-hardness, the problem for large-sized instances is computationally intractable. Thus, we develop a logic-based benders decomposition algorithm (LBBD) to solve it. First, we exploit a generalized decomposition of this problem into a relaxed main problem (RMP) and a sub-problem (SP). Solving the former allocates slabs to each crane. Then, the sequence of the assigned slabs can be found by solving its corresponding sub-problem. Finally, to verify the effectiveness of LBBD, we identify a lower bound (LB) of the optimal objective function. The problem instances on real data from an iron and steel plant are created. The result of LBBD is close to such lower bound and can be found efficiently. Note to Practitioners-This work deals with a crane assignment problem with multiple cranes for handling input slabs in a slab yard. This problem is formulated as an MILP model to minimize the completion time. Its time complexity grows exponentially with the problem size. Thus, we develop a LBBD to solve it. The numerical results reveal that LBBD can find the optimal or near-optimal solution for all realistic instances in affordable computational time. Its use can ensure the high utilization of cranes and efficient service in iron and steel plants.

关键词： Cranes Slabs Containers Processor scheduling Steel Production Iron Indexes Casting Logistics Slab yard multi-crane scheduling logic-based benders decomposition logistics mixed-integer linear program

来源：评论

学校读者我要写书评

暂无评论

New and tractable formulations for the eco-driving and the eco-routing-and-driving problems

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2025年第2期321卷 445-461页

作者： Wu, Fuliang Ye, Hongbo Bektas, Tolga Dong, Ming Shanghai Jiao Tong Univ Antai Coll Econ & Management 1954 Huashan Rd Shanghai 200030 Peoples R China Hong Kong Polytech Univ Dept Elect & Elect Engn Hung Hom Hong Kong 999077 Peoples R China Univ Liverpool Sch Management Chatham St Liverpool L69 7ZH England

Eco-driving and eco-routing problems are both concerned with minimizing the fuel consumption of a single vehicle;the former does so by optimizing the vehicle's speed profile on a given road segment, and the latter selects the best path for a vehicle from a given origin to a given destination. This paper studies a problem that combines the two, namely an eco-routing-and-driving problem, in which the path and the speed profile on each link of the chosen path are optimized simultaneously. Using the comprehensive modal emissions model as the fuel consumption model, this paper describes new and tractable formulations for both the ecodriving and the eco-routing-and-driving problems through discretization, convexification and approximation, leading to a linear program for the former and a mixed-integer linear program for the latter. Computational results indicate that the new formulation of the eco-driving problem yields significant reductions in the solution time as compared to alternative formulations and algorithms, and that the new formulation of the eco-routing-and-driving problem affords further reductions in fuel consumption when compared with other methods.

关键词： Eco-driving Eco-routing-and-driving problem Fuel consumption mixed-integer linear program

来源：评论

学校读者我要写书评

暂无评论

An adaptive large neighborhood search method for the AGV scheduling problem with a limited number of chargers

引用

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2025年

作者： Li, Yantong Ren, Bo Wen, Xin Chung, Sai-Ho Dalian Maritime Univ Sch Maritime Econ & Management Dalian Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Kowloon Hong Kong Peoples R China

Automated guided vehicles (AGVs) are widely used in various fields to fulfill the transportation demands of factories or workshops due to their intelligence, flexibility, and efficiency. Scheduling multiple AGVs in the operational practice under these scenarios is challenging, where charging operations must be jointly optimised with the task processing process. Most studies on the AGV scheduling problem assume that the charging station can simultaneously charge an unlimited number of AGVs, where each AGV must be fully charged upon each charging operation. We investigate a new AGV scheduling problem with a limited number of chargers and a flexible charging strategy, denoted as ASP-LC-FCS. We first formulate the problem as a mixed-integer linear program (MILP) and show that it is strongly NP-hard. We then derive a valid lower bound. Considering the NP-hardness of the problem, we then develop a tailored adaptive large neighbourhood search (ALNS) algorithm based on the problem structure. The ALNS employs a matheuristic to generate initial feasible solutions, designs problem-specific destroy and repair operators, and innovatively uses a local search mechanism to improve the solution during each iteration. Computational experiments on 729 randomly generated instances demonstrate the good performance of the proposed ALNS, which significantly outperforms the state-of-the-art commercial solver CPLEX and an adapted artificial bee colony algorithm. Besides, we apply the proposed ALNS method to solve a real industrial case to provide practical solutions and managerial insights.

关键词： AGV scheduling limited number of chargers flexible charging mixed-integer linear program adaptive large neighbourhood search

来源：评论

学校读者我要写书评

暂无评论

Robust doctor-patient assignment with endogenous service duration uncertainty and no-show behavior

引用

OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2025年 133卷

作者： Ji, Menglei Wang, Shanshan Peng, Chun Li, Jinlin China Acad Safety Sci & Technol Dept Rural Safety Beijing 100012 Peoples R China Beihang Univ Sch Econ & Management Beijing 100191 Peoples R China Beijing Jiaotong Univ Sch Econ & Management Beijing 100044 Peoples R China Beijing Inst Technol Sch Management & Econ Beijing 100081 Peoples R China

In practice, patient's service duration might be influenced by the workload of doctors who need to provide healthcare service. However, most existing studies have overlooked this correlation when scheduling patients and doctors. Motivated by this context, we incorporate the endogenous (decision-dependent) uncertain service duration, the presence of uncertainty dependent on assignment decisions, into the doctor-patient assignment problem with patient no-show behavior and propose a novel modeling framework. Specifically, we employ the distributionally robust optimization (DRO) approach that uses decision-dependent moment information to construct the ambiguity set of the service duration distribution. A novel decision-dependent DRO (DDRO) model is proposed for the doctor-patient assignment problem. The goal is to minimize the sum of the doctor's assignment cost and penalty cost and the worst-case expected cost of overtime and cancellation cost. To solve this model, we propose an effective nested column-and-constraint generation (C&CG) solution scheme. This approach involves decomposing the model into an outer-level problem and an inner-level problem, both of which can be solved using the C&CG algorithm. This nested scheme enables us to efficiently solve the model and obtain optimal solutions. Numerical results show that the algorithm can solve most realistic-sized problem instances optimally within the two-hour time limit. In addition, to show the effectiveness of our new modeling framework, we also propose the classical DRO and stochastic programming (SP) models as the benchmark models in our out-of-sample test. The extensive numerical results show that when there exists variability in service duration and robustness in the ambiguity set, our DDRO model outperforms the DRO and SP approaches. In addition, when there are relatively enough doctors, the DDRO method is the best option for decision-makers to make assignment plans. We also show that the no-show behavior fact

关键词： Robust doctor-patient assignment Two-stage distributionally robust optimization mixed-integer linear program Endogenous uncertainty Uncertain service duration No-show behavior Column-and-constraint generation

来源：评论

学校读者我要写书评

暂无评论

Estimating flexibility preferences to resolve temporal scheduling conflicts in activity-based modelling

引用

TRANSPORTATION 2024年第2期51卷 501-528页

作者： Manser, Patrick Haering, Tom Hillel, Tim Pougala, Janody Krueger, Rico Bierlaire, Michel Swiss Fed Railways SBB Hilfikerstr 1 CH-3000 Bern 65 Switzerland Ecole Polytech Fed Lausanne EPFL Transport & Mobil Lab TRANSP OR Stn 18 CH-1015 Lausanne Switzerland Univ Coll London UCL London England Tech Univ Denmark DTU Dept Technol Management & Econ DK-2800 Lyngby Denmark

This paper presents a novel activity-based demand model that combines an optimisation framework for continuous temporal scheduling decisions (i.e. activity timings and durations) with traditional discrete choice models for non-temporal choice dimensions (i.e. activity participation, number and type of tours, and destinations). The central idea of our approach is that individuals resolve temporal scheduling conflicts that arise from overlapping activities, e.g. needing to work and desiring to shop at the same time, in order to maximise their daily utility. Flexibility parameters capture behavioural preferences that penalise deviations from desired timings. This framework has three advantages over existing activity-based modelling approaches: (i) the time conflicts between different temporal scheduling decisions including the activity sequence are treated jointly;(ii) flexibility parameters follow a utility maximisation approach;and (iii) the framework can be used to estimate and simulate a city-scale case study in reasonable time. We introduce an estimation routine that allows flexibility parameters to be estimated using real-world observations as well as a simulation routine to efficiently resolve temporal conflicts using an optimisation model. The framework is applied to the full-time workers of a synthetic population for the city of Lausanne, Switzerland. We validate the model results against reported schedules. The results demonstrate the capabilities of our approach to reproduce empirical observations in a real-world case study.

关键词： Activity-based model Discrete choice Mathematical optimisation Maximum likelihood estimation mixed-integer linear program

来源：评论

学校读者我要写书评

暂无评论

Modeling Load Redistribution Attacks in Integrated Electricity-Gas Systems

引用

IEEE TRANSACTIONS ON SMART GRID 2024年第4期15卷 4115-4127页

作者： Liu, Rong-Peng Wang, Xiaozhe Zeng, Bo Zgheib, Rawad McGill Univ Dept Elect & Comp Engn Montreal PQ H3A 0E9 Canada Univ Pittsburgh Dept Ind Engn Pittsburgh PA 15106 USA Univ Pittsburgh Dept Elect & Comp Engn Pittsburgh PA 15106 USA Hydro Quebec Res Inst Varennes PQ J3X1S1 Canada

As the share of gas-fired power generation continues to increase, it is essential to consider integrated electricity-gas systems (IEGSs). However, the development of IEGSs has led to an increased reliance on cyber infrastructures, such as communication systems, which in turn makes IEGSs more susceptible to cyberattacks. This paper investigates the paradigm and stealthy conditions of load redistribution (LR) attacks on IEGSs and proposes a bilevel mixed-integer model to identify the most severe LR attack from an economic perspective. Under a mild assumption, we prove that the proposed model does not exclude any possible upper-level attack, which differs from existing models that may yield suboptimal solutions. A modified reformulation and decomposition (R&D) algorithm is developed to solve this model in a master-subproblem framework. Particularly, we design a new subproblem to address potential infeasibility issues in the master problem. Accordingly, two types of cuts are added to the master problem for ensuring algorithm feasibility and solution optimality. Testing results validate the effectiveness of the proposed model and solution method.

关键词： Pipelines Computer crime Power systems Transmission line measurements Research and development Mathematical models Load modeling Bilevel program cybersecurity integrated electricity and gas systems load redistribution attacks mixed-integer linear program

来源：评论

学校读者我要写书评

暂无评论

Moment-based distributionally robust joint chance constrained optimization for service network design under demand uncertainty

引用

OPTIMIZATION AND ENGINEERING 2024年第3期25卷 1631-1683页

作者： Zang, Yongsen Wang, Meiqin Liu, Huiqiang Qi, Mingyao Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China Shenzhen AI Rise Co Ltd Shenzhen 518066 Peoples R China Tsinghua Univ Res Ctr Modern Logist Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China

This paper proposes a distributionally robust joint chance constrained (DRJCC) programming approach to optimize the service network design (SND) problem under demand uncertainty. The distributionally robust method does not need complete distribution information and utilizes restricted historical data knowledge, which is significant in scarce data situations. The joint consideration of chance constraints enables more effective control of event probability, by which network managers can realize the purpose of controlling the overall service level of multi-commodities in a service network. DRJCC optimization can also help decision-makers adjust the network's conservativeness, robustness, and service rates by setting the probability parameters of the chance constraints. We reformulate the DRJCC model by addressing the corresponding distributionally robust joint chance constraints with the worst-case Conditional Value-at-Risk method and Lagrange duality theory. The model is approximately reformulated as a mixed-integer linear program, which is easier to solve than the mixed-integer semi-definite programming model in existing literature. We also develop two benchmark approaches for comparison: Bonferroni inequality approximation and scenario-based stochastic program. Comparative numerical studies demonstrate the robustness and the validation of the proposed formulations. A case study is conducted to demonstrate the industrial performance of the uncertain SND under the DRJCC formulation. We explore the impact of the confidence level parameter on operational cost and real service level, reveal the general correlation between them. We also extract several risk-averse managerial insights for logistics fleet managers.

关键词： Service network design Uncertain demand Joint chance constraint Distributionally robust optimization mixed-integer linear program

来源：评论

学校读者我要写书评

暂无评论

Two-indexed formulation of the traveling salesman problem with multiple drones performing sidekicks and loops

引用

OR SPECTRUM 2025年第1期47卷 67-104页

作者： Rave, Alexander Catholic Univ Eichstatt Ingolstadt Ingolstadt Sch Management Dept Operat Schanz 49 D-85049 Ingolstadt Germany

Aerial drone delivery has great potential to improve package delivery time, as drones can fly autonomously over obstacles at a possibly higher speed than trucks. The benefits of drones in delivery can even be increased in a truck-and-drone tandem where a truck carries multiple drones and releases them at advantageous places, i.e., the traveling salesman problem with multiple drones (TSPmD). We focus on a general version of this problem with makespan minimization, where the drones have two options after serving the customer: they can return to any node the truck visits at a later stage (sidekick) or return to the same node they were launched from (loop) - even at the depot. We introduce an efficient two-indexed mixed-integer linear program (MILP) for this TSPmD and show how to adapt the MILP to cover two problem variants, namely the multiple flying sidekick traveling salesman problem and the traveling salesman problem with drone. Our MILP formulation is an efficient formulation, as it outperforms eight state-of-the-art MILP formulations for these problem variants in nearly all larger instances. In a numerical study, we provide new optimal solutions with up to 28 nodes for benchmark purposes. Moreover, we analyze the impact of allowing drone loops on makespan minimization in general and at the depot. We find that loops mainly become relevant when drones travel faster than trucks, resulting in average makespan savings of up to 2.7%.

关键词： Unmanned aerial vehicles Routing Last-mile delivery mixed-integer linear program Benchmark instances

来源：评论

学校读者我要写书评

暂无评论

Distributional utility preference robust optimization models in multi-attribute decision making

引用

MATHEMATICAL programMING 2024年 1-47页

作者： Hu, Jian Zhang, Dali Xu, Huifu Zhang, Sainan Univ Michigan Dearborn Dept Ind & Mfg Syst Engn Dearborn MI 48128 USA Shanghai Jiao Tong Univ Sino US Global Logist Inst Antai Coll Econ & Management Shanghai 200030 Peoples R China Chinese Univ Hong Kong Dept Syst Engn & Engn Management Shatin Hong Kong Peoples R China

Utility preference robust optimization (PRO) has recently been proposed to deal with optimal decision-making problems where the decision maker's (DM's) preference over gains and losses is ambiguous. In this paper, we take a step further to investigate the case that the DM's preference is random. We propose to use a random utility function to describe the DM's preference and develop distributional utility preference robust optimization (DUPRO) models when the distribution of the random utility function is ambiguous. We concentrate on data-driven problems where samples of the random parameters are obtainable but the sample size may be relatively small. In the case when the random utility functions are of piecewise linear structure, we propose a bootstrap method to construct the ambiguity set and demonstrate how the resulting DUPRO can be solved by a mixed-integer linear program. The piecewise linear structure is versatile in its ability to incorporate classical non-parametric utility assessment methods into the sample generation of a random utility function. Next, we expand the proposed DUPRO models and computational schemes to address general cases where the random utility functions are not necessarily piecewise linear. We show how the DUPRO models with piecewise linear random utility functions can serve as approximations for the DUPRO models with general random utility functions and allow us to quantify the approximation errors. Finally, we carry out some performance studies of the proposed bootstrap-based DUPRO model and report the preliminary numerical test results. This paper is the first attempt to use distributionally robust optimization methods for PRO problems.

关键词： PRO Multi-attribute decision-making Piecewise linear random utility function Bootstrap ambiguity set mixed-integer linear program 90-10

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

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

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：