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检索条件"任意字段=13th International Conference on Integer Programming and Combinatorial Optimization"

共 741 条记录，以下是711-720 订阅

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Coordinated Earth Observation Task Scheduling Algorithm for Multiple Controlling Platforms 3rd

Coordinated Earth Observation Task Scheduling Algorithm for ...

引用

3rd international conference on Space Information Networks, SINC 2018

作者： Wu, Jiaxin Liu, Runzi Sheng, Min Li, Jiandong Chi, Kai Tian, Wanyong The State Key Lab of ISN Xidian University Xi’anShaanxi710071 China Electric Information Network Laboratory CETC the 20th Research Institute Xi’anShaanxi710068 China

ISBN: (纸本)9789811359361

In view of the current situation that different Earth Observation Satellite systems are independent in our country, which results in the failure to share resources and to cope with numerous emergency tasks effectively, the paper proposes a Multi-platform Distributed Coordinate Task Scheduling Algorithm (MDCTS Algorithm) via consensus ADMM (Alternating Direction Method of Multipliers). Firstly, the problem of maximizing the overall value of multi-platform is modelled as a mixed-integer linear programming problem. then, the global optimization problem is decomposed into the scheduling of each platform based on local information and public task price issued by collaborative center. On the basis, MDCTS Algorithm is proposed. the simulation results show that compared to existing algorithm, the value of local and public tasks achieved by MDCTS Algorithm is higher under the premise that the local tasks and resource information of each controlling platform do not have to be disclosed. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Global optimization

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A MIP Approach to the Yearly Scheduling Problem of a Mixed Hydrothermal System

A MIP Approach to the Yearly Scheduling Problem of a Mixed H...

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5th international conference on the European Electricity Market (EEM 2008), vol.2

作者： Costas G. Baslis Anastasios G. Bakirtzis Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece

this paper presents a mixed-integer optimization approach to the yearly hydrothermal scheduling problem. the proposed method is applied to a hydrothermal system comprising 29 thermal units and 13 hydroplants, including 2 pumped storage plants, similar to the Greek Power System. the generation scheduling model is based on an hourly load curve. Perfect competition assumption is adopted and all thermal generators are assumed to bid their marginal cost. A large mixed-integer programming problem is formulated and implemented in GAMS. Binary variables represent thermal unit hourly commitment status. Results on an hourly basis, including thermal unit commitment and dispatch, hydroplant generation and pumping and system marginal price are presented.

关键词： Hydrothermal scheduling Mixed-integer programming Perfect competition

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Multiobjective Branch-and-Cut Method with Shared Cutting Plane Information: A Case Study on Optimizing Garbage Collection

Multiobjective Branch-and-Cut Method with Shared Cutting Pla...

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international Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Tomoki Kaho Kazutoshi Sakakibara Mikiharu Arimura Shinya Watanabe The Graduate School of Engineering Muroran Institute of Technology Muroran Japan Department of Data Science Faculty of Information Engineering Toyama Prefectural University Toyama Japan Department of Engineering Muroran Institute of Technology Muroran Japan Department of Sciences and Informatics Muroran Institute of Technology Muroran Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

this paper presents an application of the Multi-Objective Branch-and-Bound based on Decomposition (MOBB/D) method for Branch-and-Cut, combining branch-and-bound and cutting-plane methods. Traditionally, multi-objective branch-and-bound methods for multi-objective mixed-integer linear programming problems struggle with the large number of Pareto-optimal solutions. MOBB/D addresses this by decomposing multi-objective problems into single-objective subproblems using weight vectors and applying branch-and-bound to each, with information sharing between nearby subproblems. In this paper, we customize the MOBB/D method for Branch-and-Cut to achieve an efficient search by sharing cutting plane information in MOBB/D. We demonstrate our approach with a case study on garbage collection planning in Muroran City, Hokkaido, Japan. this case study combines facility location and route optimization within a multi-objective framework, balancing the burdens on residents and garbage collection workers. Numerical experiments compare execution times and solutions with and without cutting plane sharing, and visualize the impact of different objective balance preferences on route optimization. the results show substantial efficiency gains and provide practical insights for multi-objective optimization in urban planning.

关键词： Visualization Scalability Roads Urban planning Vectors Real-time systems Planning Mixed integer linear programming Computational efficiency optimization

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Learning Heuristics Approaches in Mixed integer Linear Programing

Learning Heuristics Approaches in Mixed Integer Linear Progr...

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international conference on Computers, Communications, and Systems (ICCCS)

作者： Zhilei Wang Wentao Song Yang Lei Yu Wang Naijie Gu School of Computer Science and Technology University of Science and Technology of China Hefei China School of Data Science University of Science and Technology of China Hefei China

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

Mixed integer Linear programming (MILP) technology is a versatile method used for formulating and solving combinatorial optimization problems. During the solving process, primal heuristics help to quickly find good feasible solutions, which can aid branch-and-bound (B&B) algorithms in reducing the primal-dual gap and pruning the B&B search tree. the heuristics employed by existing open-source solvers follow empirical rules summarized from real-world instances, enabling the solvers to achieve generally good performance but sometimes performing poorly on specific instances. In response, this paper proposes a method that uses hierarchical sequence models to learn the patterns of given instances and assigns a heuristic configuration for them. Compared to the default settings of the solver, the proposed method enables heuristic module to perform better, finding feasible solutions more quickly and reducing the primal-dual gap. Experimental results indicate that the proposed method can improve the solver's average performance on given instances by 27%.

关键词： Communication systems Heuristic algorithms Reinforcement learning Manuals Mixed integer linear programming Task analysis optimization

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Scheduling for last-mile meal-delivery processes 9

Scheduling for last-mile meal-delivery processes

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9th IFAC/IFIP/IFORS/IISE/INFORMS conference on Manufacturing Modelling, Management and Control (IFAC MIM)

作者： Cosmi, Matteo Nicosia, Gaia Pacifici, Andrea Univ Roma Tre Dipartimento Ingn Via Vasca Navale 79 I-00146 Rome Italy Univ Roma Tor Vergata Dipartimento Ingn Civile & Ingn Informat Via Politecn 1 I-00133 Rome Italy

We address a single machine scheduling problem arising in a last mile delivery setting for a food company. the same problem finds obvious applications also in the context of internal manufacturing logistics. A set of food orders are placed by the customers and are to be fulfilled by the company. Each order comprises a delivery point and an ideal delivery time An order is considered on time if it is delivered within a certain given time interval around the ideal delivery time. All food is prepared in a single production facility (restaurant) and immediately carried to the customers by a single courier, who may dispatch one or two different orders in a single trip. Since late deliveries correspond to canceled orders and an economic loss for the company, it is of interest to schedule orders so that the number of late orders is minimized. We model the resulting decision problem as a special single machine scheduling problem and propose different mixed integer programs to solve it. their performance is assessed through a computational study on a set of test instances derived by our real-world application. (C) 2019, IFAC (international Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Scheduling integer programming optimization Problems combinatorial Mathematics Internal Logistics Food Delivery

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Optimal Application Deployment in Mobile Edge Computing Environment

Optimal Application Deployment in Mobile Edge Computing Envi...

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IEEE international conference on Cloud Computing, CLOUD

作者： Feifei Chen Jingwen Zhou Xiaoyu Xia Hai Jin Qiang He School of Information Technology Deakin University Geelong Australia School of Computer Science and Technology Huazhong University of Science and Technology China School of Computer Science Chengdu University of Information Technology China

ISBN: (数字)9781728187808

ISBN: (纸本)9781728187815

Mobile edge computing has emerged as a new distributed computing paradigm that overcomes the limitations of traditional cloud computing. In an edge computing environment, an app vendor can hire computing and storage resources on edge servers for deploying their applications to deliver lower-latency services to their app users. Under a budget constraint, an optimal edge application deployment strategy allows an app vendor to deploy application instances on edge servers in a specific area and provide services to the most app users in the area. In this paper, we make the first attempt to tackle this edge application deployment (EAD) problem. Specifically, we formulate the EAD problem as a constrained optimization problem and prove its NP-hardness. then, we propose an optimal approach named EAD-opt to find the optimal solution of EAD based on integer programming, and an approximation approach named EAD-apx to find approximate solutions in large-scale EAD scenarios efficiently. We evaluate our approaches by conducting experiments on a widely used real-world data set and a synthetic data set with comparison against two baseline approaches. the experimental results demonstrate that our approaches can solve the EAD problem effectively and efficiently.

关键词： integer programming Cloud computing conferences Servers Distributed computing optimization Edge computing

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Maximizing Profit in Energy-Efficient Moldable Task Execution with Deadline

Maximizing Profit in Energy-Efficient Moldable Task Executio...

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Euromicro conference on Parallel, Distributed and Network-Based Processing

作者： Sebastian Litzinger Jörg Keller Christoph Kessler Faculty of Mathematics and Computer Science FernUniversität in Hagen Hagen Germany Dept. of Computer and Information Science (IDA) Linköping University Linköping Sweden

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

We consider static scheduling of parallelizable tasks onto machines with frequency scaling for the case that not all tasks can be executed prior to a deadline. We model this scenario from a HPC cluster operator's perspective. We solve the combinatorial optimization problem to maximize the operator's profit by integer linear programming and by a heuristic. We evaluate the heuristic with synthetic benchmark task sets and demonstrate that it achieves at most 20 % less profit than the solution via linear programming, so that it can be used for large task sets where the latter is not feasible anymore.

关键词： Task analysis Schedules optimization Parallel machines Program processors Runtime Radio spectrum management

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A Joint Order Cost optimization Model for Multi-Item Spare Parts Manufacturing Systems Considering the Requirement of Support Probability

A Joint Order Cost Optimization Model for Multi-Item Spare P...

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international conference on Automation and Computing (ICAC)

作者： Xinhao Cui Ruiyi Yang Siyue Zhang Yiyong Xiao School of Reliability and Systems Engineering Beihang University Beijing China

Reducing the comprehensive cost of spare parts is one of the main objectives of cost-optimized design for manufacturing systems (MSs). For multi-item MSs, there are usually more variables in the composition of spare parts costs, such as purchase and inventory costs. Besides, the coupling and interaction between these variables have an impact on the final spare parts cost, forming a more complex combinatorial optimization problem. Moreover, the ordering activities of spare parts are scattered in the time window between each period, and the order quantity and timing can significantly impact the cost. To solve this problem, this paper proposes a joint ordering cost optimization model that considers the requirement of support probability. In this paper, a mixed integer linear programming model (MILP) is established for the specific problem. Finally, numerical examples are synthesized based on actual records to verify the feasibility and rationality of the model. the results also show that the proposed model significantly reduces the total spare parts costs of MSs.

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Model and combinatorial optimization Methods for Tactical Planning in Closed-Loop Supply Chains

Model and Combinatorial Optimization Methods for Tactical Pl...

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international conference on Tools with Artificial Intelligence

作者： Pierre Desport Anne Liret Frederic Lardeux Carla Di Cairano-Gilfedder David Lesaint Gilbert Owusu LERIA Univ. d'Angers Angers France BT France France BT Group plc Ipswich UK

ISBN: (纸本)9781509044603

Distribution planning in closed-loop supply chains is concerned with determining transfer and repair operations based on demand forecasts and subject to backordering, inventory, transfer and repair constraints. We present a mixed-integer programming model and a dedicated metaheuristics for this problem and show it is is NP-hard. the model is applicable to a wide range of closed-loop supply chains with different network topologies and site functions and it can also support different planning strategies by means of a weighted objective function. Comparative experiments on pseudo-random instances built on a case study in telecommunication service operations demonstrate the effectiveness and scalability of the metaheuristics. Lastly, we discuss possible extensions to address common supply chain requirements, including the ability to produce robust plans in uncertain environments.

关键词： Maintenance engineering Planning Supply chains Electronic mail Topology Linear programming

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Structural analysis of branch-and-cut and the learnability of gomory mixed integer cuts 22

Structural analysis of branch-and-cut and the learnability o...

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Proceedings of the 36th international conference on Neural Information Processing Systems

作者： Maria-Florina Balcan Siddharth Prasad Tuomas Sandholm Ellen Vitercik School of Computer Science Carnegie Mellon University Computer Science Department Carnegie Mellon University Computer Science Department Carnegie Mellon University Optimized Markets Inc. Strategic Machine Inc. Strategy Robot Inc. Management Science and Engineering Department Computer Science Department Stanford University

ISBN: (纸本)9781713871088

the incorporation of cutting planes within the branch-and-bound algorithm, known as branch-and-cut, forms the backbone of modern integer programming solvers. these solvers are the foremost method for solving discrete optimization problems and have a vast array of applications in machine learning, operations research, and many other fields. Choosing cutting planes effectively is a major research topic in the theory and practice of integer programming. We conduct a novel structural analysis of branch-and-cut that pins down how every step of the algorithm is affected by changes in the parameters defining the cutting planes added to an integer program. Our main application of this analysis is to derive sample complexity guarantees for using machine learning to determine which cutting planes to apply during branch-and-cut. these guarantees apply to infinite families of cutting planes, such as the family of Gomory mixed integer cuts, which are responsible for the main breakthrough speedups of integer programming solvers. We exploit geometric and combinatorial structure of branch-and-cut in our analysis, which provides a key missing piece for the recent generalization theory of branch-and-cut.

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