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检索条件"主题词=MIXED integer linear programming"

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Mathematical Models for Finding the Shortest Cycle to Visit a Given Number of Vertices from the Graph Clusters

Mathematical Models for Finding the Shortest Cycle to Visit ...

引用

Problems of Logistics, Management and Operation in the East-West Transport Corridor (PLMO), International Conference on

作者： Petro Stetsyuk Mykola Korablov Oleksandr Stoian Oleh Hubernator Department of Nonsmooth Optimization Methods V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine Kyiv Ukraine Faculty of Radiophysics Electronics and Computer Systems Taras Shevchenko National University of Kyiv Kyiv Ukraine

ISBN: (数字)9798350353099

ISBN: (纸本)9798350353105

Travelling Salesman Problem (TSP) is known for its numerous modifications and applications in different areas. Introduced in this paper are the problem of finding the shortest cycle through a given number of vertices from the graph clusters and two mixed integer linear programming (MILP) models for solving the problem. The first MILP model is based on the generalized version of Miller, Tucker and Zemlin constraints for standard TSP. The second model is based on the generalized version of Gavish and Graves constraints for standard TSP. Necessity and sufficiency of models constraints are proved. Results of a computational experiment are presented.

关键词： Sequential analysis Computational modeling Routing Mathematical models mixed integer linear programming Servers Standards Logistics

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Data-driven Acceleration Method for Discrete Interprovincial Medium and Long-term Power Transactions Clearing Problem

Data-driven Acceleration Method for Discrete Interprovincial...

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Power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Qian Gao Zhifang Yang Haihua Cheng Wenyuan Li Ziqing Zhou Hui Deng State Key Laboratory of Power Transmission Equipment Technology Chongqing University Chongqing China China Electric Power Research Institute Nanjing China Power Market Simulation Laboratory State Grid Zhejiang Electric Power CO. LTD. Research Institute Hangzhou China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

The optimization of the interprovincial medium and long-term power transactions clearing problem aims to maximize social welfare through the selection of optimal purchasing and selling pairs. Considering the extensive range of time periods, buyers, sellers, transmission paths, and the discrete nature of selling in blocks, it is intractable to obtain the optimal solution within a practical computing time limit, even using the state-of-the-art discrete optimizer. To address this challenge, this paper proposes a data-driven approach to accelerate the solution process by fully exploring few-shot historical data. First, the stable structure of the solution pattern is identified and fixed in advance to reduce the model scale. Second, multiple warm-start solutions are selected using the bidding price feature. Finally, the solution process is accelerated to achieve an improved decision. Based on practical data in China, the case study demonstrates that the proposed method can improve the solution quality by 1 million RMB on average within the solution time limit of 1 hour, compared with directly solving the clearing problem using the state-of-the-art commercial solver.

关键词： Electrical engineering Computational modeling Asia Power systems mixed integer linear programming Optimization

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A MILP Scheduling Problem for Multi-Robot Logistics Systems in a Precision Farming Application and a Polynomial Time Optimal Algorithm

A MILP Scheduling Problem for Multi-Robot Logistics Systems ...

引用

Mediterranean Conference on Control and Automation (MED)

作者： Antonio Furchì Mauro Franceschelli Andrea Gasparri Department of Civil Computer Science Aeronautical Technologies Engineering Roma Tre University Roma Italy University of Cagliari Italy

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

In this paper, we present an innovative use of multi-robot systems in a precision farming application proposed in the European project “CANOPIES”. The considered scenario is then formalized identifying a real-time scheduling problem that needs to be solved for the efficient use of the multi-robot platform. A solution to the proposed real-time scheduling problem is first identified by proposing a mixed integer linear programming (MILP) problem formulation which is iteratively solved within a receding horizon time window. Then, we propose a polynomial time optimal algorithm able to solve a simplified but relevant scenario of the proposed multi-robot scheduling problem. Numerical examples are presented to corroborate the formal analysis of the proposed algorithm.

关键词： Sufficient conditions Europe Polynomials Scheduling Real-time systems mixed integer linear programming Multi-robot systems

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Exact resolution for the unrelated parallel machine scheduling problem with flexible maintenance and human operators planning

Exact resolution for the unrelated parallel machine scheduli...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Meriem Touat Computer Science and Digital Society (LIST3N) Université de Technologie de Troyes Troyes France

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This study addresses a novel parallel machine scheduling problem where machines undergo periodic, flexible maintenance needing human operators. Operators differ in competence and availability, affecting maintenance execution and planning feasibility. We focus on optimizing a weighted objective function encompassing both production and maintenance. Indeed, we aim to minimize the sum of production tardiness and the maintenance earliness-tardiness. To tackle this problem, we introduce two mathematical models: one based on mixed-integer linear programming (MILP) and the other on Constraint programming (CP). Both models are solved using IBM ILOG Cplex 22.1, demonstrating the effectiveness of the CP modelling in managing this complex scheduling problem.

关键词： Constraint handling Production Parallel machines programming linear programming Mathematical models Maintenance Planning mixed integer linear programming Information technology

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A heuristic approach to optimize radial inter-array cabling topologies in large wind power plants

A heuristic approach to optimize radial inter-array cabling ...

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IEEE General Meeting Power& Energy Society

作者： Ramon Abritta Alexey Pavlov Damiano Varagnolo Børre Tore Børresen Dept. of Geoscience and Petroleum Norwegian University of Science and Technology Trondheim Norway Dept. of Engineering Cybernetics Norwegian University of Science and Technology Trondheim Norway Research Center Equinor ASA Trondheim Norway

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

We propose and analyze an algorithm for planning the topology of the inter-array cables that, in a wind power plant (WPP), link the wind turbine generators (WTGs) to the substation. The approach embeds a heuristic step that significantly reduces the complexity of planning the radial inter-array cable topology for large WPPs, which is generally an NP-hard mixed-integer linear programming problem. The heuristic seeks to reduce the number of decision variables by utilizing user-defined parameters to exploit characteristics of the WPPs layouts. We demonstrate the effectiveness of the heuristic by comparing its cost-saving potentials against another state-of-the-art method on three use-cases regarding real WPPs. In terms of solution quality, the results indicate that, among all study cases, the proposed strategy either compares favorably or has a similar performance to the method from the literature.

关键词： Substations Layout Voltage Wind power generation Generators Topology Planning Wind turbines mixed integer linear programming Cables

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Energy Management System for the CN MOST Laboratory at the Savona University Campus

Energy Management System for the CN MOST Laboratory at the S...

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IEEE International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI)

作者： Matteo Fresia Tommaso Robbiano Silvia Siri Stefano Bracco DITEN department University of Genoa Genova Italy DIBRIS department University of Genoa Genova Italy

ISBN: (数字)9798350362138

ISBN: (纸本)9798350362145

This paper proposes a mixed-integer linear programming model for the energy management system of the new research laboratory that will be installed in the Savona Campus of the University of Genova, benefitting from the fundings of the Italian National Center for Sustainable Mobility. This energy management system is able to daily manage the nanogrid feeding the laboratory which will be equipped with a photovoltaic plant and a battery energy storage system, and will have to feed electric loads of the laboratory and a set of autonomous mobile robots used to execute different delivery tasks within the campus. The proposed energy management system optimizes power flows and robot task scheduling in order to minimize the operating costs, the curtailment of the photovoltaic source and the number of unperformed tasks. The application of the proposed mathematical formulation to the real case of the Savona Campus is presented and discussed in the paper.

关键词： Photovoltaic systems Technological innovation Uncertainty Service robots Real-time systems Mathematical models mixed integer linear programming Mobile robots Energy management systems Optimization

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Integrated Optimization on Tugboat Scheduling and Berth Allocation of Seaside Port Operations

Integrated Optimization on Tugboat Scheduling and Berth Allo...

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Automation in Manufacturing, Transportation and Logistics (ICaMaL), International Conference on

作者： Mingkai Zou Yaqiong Lv School of Transportation and Logistics Engineering Wuhan University of Technoloty Wuhan China

ISBN: (数字)9798350378658

ISBN: (纸本)9798350378665

The current inefficiency in seaside operations at the port terminal has led to excessive waiting times for ships and environmental pollution. Traditional decision-making methods for berth allocation and tug scheduling plans have resulted in inefficiencies in the overall integrated process. In this study, a new mixed-integer linear programming model for optimizing tugboat scheduling and berth allocation at seaside port terminals is presented, aiming to minimize the weighted total stay time of ships while addressing the complexities of tugboat matching constraints, ship shift movements, and the heterogeneity of berths. Through computational experiments utilizing both practical port data and randomly generated instances, the model demonstrates significant improvements in operational efficiency and environmental impact reduction compared to traditional port scheduling methods. By focusing on the optimization of resource allocation and scheduling, the proposed model offers a comprehensive solution to the current inefficiencies faced by port terminals, highlighting its potential for practical implementation and its contribution towards more sustainable and effective port operations.

关键词： Job shop scheduling Pollution Processor scheduling Computational modeling Seaports mixed integer linear programming Manufacturing Resource management Marine vehicles Optimization

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Vehicle Routing Problem with Synchronization for Mobile Health Clinics

Vehicle Routing Problem with Synchronization for Mobile Heal...

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IEEE International Technology Management Conference

作者： Faisal Alkaabneh Sam Jotham Sutharson Industrial Engineering American University of Sharjah Sharjah United Arab Emirates Industrial & Systems Engineering North Carolina A&T State University Greensboro North Carolina USA

ISBN: (数字)9798350367355

ISBN: (纸本)9798350367362

As an important means of providing medical services in developing countries and remote areas, Mobile Health Clinics (MHCs) focus on distributing medical supplies and providing basic health needs to underserved communities. We model this problem as a vehicle routing problem with multiple synchronization constraints and heterogeneous demand (VRPMSC-HD) and formulate a mixed integer linear programming (MILP). We propose a matheuristic based on adaptive large neighborhood search (ALNS) combined with an intensive local search phase to solve large-scale instances on the model. We assess the advantages and disadvantages of the proposed approach by comparing its solutions with the solutions of the vehicle routing problem with multiple trips (VRP-MT). Interestingly, the proposed approach leads to longer total traveled distance/time when taking into account the routing of the resupply truck and the MHCs. On the other hand, the proposed approach achieves significant reduction in the latest arrival metric leading to faster completion of services and higher utilization of a fleet of MHCs.

关键词： Measurement Adaptation models Technology management Vehicle routing Metaheuristics Medical services Routing Mathematical models mixed integer linear programming Synchronization

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Multi-Objective Service Restoration and Visualization for increased Distribution System Resiliency

Multi-Objective Service Restoration and Visualization for in...

引用

IEEE General Meeting Power& Energy Society

作者： Tumininu Mbanisi Dongyun Han Isaac Cho Valentina Cecchi Department of Electrical and Computer Engineering Department of Computer Science Utah State University Logan UT USA Department of Computer Science The University of North Carolina at Charlotte Energy Production and Infrastructure Center The University of North Carolina at Charlotte Charlotte NC USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

In the face of increasing billion-dollar weather events in the United States, grid resilience has become a central issue for electric utilities, operators and customers. Hence, this work presents service restoration and data-enhanced visualization for improved decision-making and resilience in the distribution system. First, we present an exploratory visual interface that increases situational awareness in the distribution system by allowing system operators to glean actionable intelligence from historical outage data. In addition, this study proposes a prescriptive service restoration framework that allows distribution system operators to manage outages in a proactive manner by leveraging outage forecasts to minimize out-of-service loads in the event of predicted outages in the distribution network. The proposed framework is formulated as a mixed integer linear programming problem and is validated using a modified IEEE 13-node test feeder. Results show a decrease in the impact of predicted outages as a result of implementing the topology optimization and service restoration framework.

关键词： Visualization Network topology Distribution networks Power industry Topology mixed integer linear programming Optimization Faces Resilience Meteorology

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A GCN-Based Adaptive Large Neighbourhood Search for Multi-Depot Vehicle Routing Problem in Airport Ground Handling

A GCN-Based Adaptive Large Neighbourhood Search for Multi-De...

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Artificial Intelligence Technology (ACAIT), Asian Conference on

作者： Fei Xiang Mingjie Tang Bo Wen Runhao Xu Junda Chen Jie Chen Civil Aviation Chengdu Information Technology Co. Ltd The Second Research Institute of Civil Aviation Administration of China Chengdu China

ISBN: (数字)9798331517090

ISBN: (纸本)9798331517106

Airport ground handling (AGH) is crucial for enhancing the efficiency of airport operations and contributing to the economic viability of the aviation industry. Multi-depot vehicle routing is a typical type of problem in AGH, and owing to the substantial increase in flight numbers, there is a considerable challenge in scheduling vehicles from multiple depots to service the high volume of flights. To deal with this problem, a novel GCN-based adaptive large neighbourhood search (ALNS) method is proposed in this paper. We first formulate the multi-depot vehicle routing problem (MDVRP) as a mixed integer linear programming (MILP) model, then solve it with the proposed ALNS method. By providing the graphical depiction of the MILP model, we incorporate supervised learning with graph convolutional network (GCN) to train a destroy-operator for the automatic selection of variables, and leverage greedy insertion and regret value insertion as repair-operation to generate new solution. Extensive experimental evaluations illustrate the superiority of our method over state-of-the-art meta-heuristics and commercial solvers. The improved performance indicates that our approach effectively addresses the MDVRP, contributing to enhanced operational efficiency in AGH.

关键词： Adaptation models Job shop scheduling Graph convolutional networks Vehicle routing Supervised learning Metaheuristics Reinforcement learning Airports Search problems mixed integer linear programming

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