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Leveraging duality for the gamma-robust segment routing traffic engineering problem

DISCRETE APPLIED MATHEMATICS 2025年 364卷 199-212页

作者： Callebaut, Hugo De Boeck, Jerome Fortz, Bernard Univ Libre Bruxelles Dept Informat B-1050 Brussels Belgium Univ Liege HEC Liege Management Sch B-4000 Liege Belgium Inria INOCS F-59650 Villeneuve Dascq France

Segment Routing (SR), a modern network architecture enhancing traffic engineering, offers flexibility by allowing traffic to be routed through intermediate nodes or links. This paper addresses the challenge of optimizing routing in uncertain traffic distribution scenarios. Rather than relying on a single traffic matrix for optimization, we take a unique approach, considering an infinite set of matrices defined by linear constraints. Our goal is to optimize routing strategies under the worst-case scenario within this set. Through novel formulations, we achieve significant improvements in optimization speed compared to traditional methods that explore all extreme points or use iterative constraint generation for these matrices. This research contributes to the field by enhancing the robustness of SR-based traffic engineering, an area previously explored using different methodologies. (c) 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Segment routing Traffic engineering Robust optimization mixed integer linear problem

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Multi-objective flexible flow lines with due window, time lag, and job rejection

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2013年第9-12期64卷 1423-1433页

作者： Sheikh, Shaya Case Western Reserve Univ Cleveland OH 44106 USA

This paper presents a multi-objective flexible flow shop scheduling problem with limited time lag between stages. n jobs are available to schedule in a predetermined due window. A mixed integer linear programming model with the objectives of maximizing the total profit gained from scheduled jobs and minimizing deviation from the due date is introduced. Due to non-deterministic polynomial-time-hard complexity, the problem is solved with an efficient genetic algorithm. A heuristic mechanism is devised in every generation of the genetic algorithm to assure the solution feasibility. This heuristic also decreases the total solution time by reducing the search space. Computational results show that the presented approach finds solutions of good quality in reasonable runtimes.

关键词： Flexible flow line Time windows Time lag (buffer) Genetic algorithms Multi-objective mixed integer linear problem

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Simultanous emergency demand response programming and unit commitment programming in comparison with interruptible load contracts

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IET GENERATION TRANSMISSION & DISTRIBUTION 2012年第7期6卷 605-611页

作者： Sahebi, M. M. Duki, E. A. Kia, M. Soroudi, A. Ehsan, M. Sharif Univ Technol Ctr Excellence Power Syst Management & Control Tehran Iran

Different reasons such as power system restructuring, electricity price variation in some hours of a day and growth in the fuel price, have led to more attention to demand response (DR) programmes for consumers. Two important issues in DR programmes are emergency demand response programming (EDRP) and Interruptible/Curtail able (I/C) programme that is utilised as interruptible load contracts (ILC). The EDDR is utilised to decrease the consumption in peak load or critical hours of the day. This occurs by means of customer's behaviour in response to the incentives. However, the curtailment of voluntarily loads in the critical hours considering the consumer requirements is an action that can be performed in DR. A model has been proposed for EDRP and ILC implementation in the unit commitment (UC) programme. Then, the effect of these two DR programmes have been compared in long-term UC problem with fuel constraints. The proposed methodology has been formulated as a mixed integer linear problem and implemented in GAMS environment. The proposed model is applied to a 6-bus test system and a modified IEEE 118-bus system to demonstrate its effectiveness.

关键词： Power system management, operation and economics linear programming Optimisation techniques power markets power system restructuring ILC EDRP fuel price integer programming contracts mixed integer linear problem interruptible-curtail programming 6-bus test system power generation scheduling emergency demand response programming IEEE standards peak load consumption power generation dispatch I-C programming electricity price variation GAMS environment Generating stations and plants UC programming unit commitment programming modified IEEE 118-bus system interruptible load contract

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A MILP approach combined with clustering to solve a special petrol station replenishment problem

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CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH 2024年第1期32卷 95-107页

作者： Hajba, Tamas Horvath, Zoltan Heitz, Daniel Psenak, Balint Szecheny Istvan Univ Gyor Hungary Morgan Stanley Hungary Budapest Hungary MediaCom GmbH Vienna Austria

Vehicle routing problem is a well-known optimization problem in the logistics area. A special case of the vehicle routing problem is the station replenishment problem in which different types of fuel types have to be transported from the depots to the customers. In this paper we study the replenishment problem of a European petrol company. The problem contains several additional constraints such as time windows, different sized compartment vehicles, and restrictions on the vehicles that can serve a customer. We introduce a mixed integer linear programming model of the problem. To reduce the size complexity of the MILP model the customers are clustered and, based on the clusters, additional constraints are added to the MILP model. The resulting MILP model is tested on real problems of the company. The results show that combining the MILP model with clustering improves the effectiveness of the model.

关键词： Vehicle routing Petrol station replenishment mixed integer linear problem Clustering

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A Mathematical Modeling for Contract Flexibility Optimization by Brazilian Free Consumers

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IEEE LATIN AMERICA TRANSACTIONS 2020年第9期18卷 1530-1537页

作者： Takigawa, F. Y. K. Scuzziato, M. R. Tenfen, D. Fernandes, R. C. Inst Fed Santa Catarina IFSC Dept Acad Eletrotecn Itajai SC Brazil

In Brazil, free consumers must follow the criteria established by Law 9.074/95 and participate in the Free Contracting Environment (ACL), regulated by Decree 5.163/04, together with energy generators, traders, importers and exporters. These free consumers can choose and negotiate their energy purchase contracts (energy volumes, contract terms, prices, flexibilization and financial guarantees) with the other agents connected to the interconnected Brazilian grid. However, free consumers must have 100% of its energy contracted to avoid exposure to the short-term market and possible penalties, among others points. It is noteworthy that free consumers in Brazil are usually large industries and use electricity energy only to manufacture their products. In this sense, they are totally averse to contractual risks and penalties and seek the ACL only to obtain financial reductions with the same contractual security as the regulated market. In this sense, the main objective of this work is to model the mathematical optimization problem for contract flexibility optimization by free consumer in the ACL, minimizing the energy cost to meet its demand.

关键词： Contracts Optimization Mathematical model IEEE transactions Security Industries Indexes energy environment energy purchase contract free consumer mixed integer linear problem Brazilian energy environments Free Contraction Environment

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Math-based reinforcement learning for the adaptive budgeted influence maximization problem

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NETWORKS 2024年第3期83卷 547-569页

作者： Fadda, Edoardo Di Corso, Evelina Brusco, Davide Aelenei, Vlad Stefan Rares, Alexandru Balan Politecn Torino Dept Math Sci Turin Italy ISIRES Ist Italiano Ric & Sviluppo Turin Italy Politecn Torino Dept Math Sci Corso Duca Abruzzi 24 I-10129 Turin Italy

In social networks, the influence maximization problem requires selecting an initial set of nodes to influence so that the spread of influence can reach its maximum under certain diffusion models. Usually, the problem is formulated in a two-stage un-budgeted fashion: The decision maker selects a given number of nodes to influence and observes the results. In the adaptive version of the problem, it is possible to select the nodes at each time step of a given time interval. This allows the decision-maker to exploit the observation of the propagation and to make better decisions. This paper considers the adaptive budgeted influence maximization problem, that is, the adaptive problem in which the decision maker has a finite budget to influence the nodes, and each node requires a cost to be influenced. We present two solution techniques: The first is an approximated value iteration leveraging mixed integer linear problems while the second exploits new concepts from graph neural networks. Extensive numerical experiments demonstrate the effectiveness of the proposed approaches.

关键词： adaptive budgeted influence maximization problem approximate dynamic programming graph neural networks mixed integer linear problem reinforcement learning two-stage stochastic problem

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Enhancing Grid-Connected Microgrid Power Dispatch Efficiency Through Bio-Inspired Optimization Algorithms

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IEEE ACCESS 2024年 12卷 23578-23594页

作者： Fatima, Itrat Alqahtani, Jarallah Habib, Raja Akram, Muhammad Naz, Tabbasum Alqahtani, Ali Atif, Muhammad Alyami, Sultan S. Capital Univ Sci & Technol Dept Software Engn Islamabad 44000 Pakistan Najran Univ Coll Comp Sci & Informat Syst Dept Comp Sci Najran 61441 Saudi Arabia Shifa Tameer E Millat Univ Dept Comp Islamabad 44000 Pakistan Univ Strathclyde Technol & Innovat Ctr CMAC Future Mfg Res Hub Glasgow G1 1RD Lanark Scotland Najran Univ Coll Comp Sci & Informat Syst Dept Networks & Commun Engn Najran 61441 Saudi Arabia Univ Lahore Dept Comp Sci & IT Lahore 54000 Pakistan

This work tackles the scheduling challenge of microgrids for smart homes, aiming to optimize energy management with both renewable and non-renewable sources. A power control center orchestrates the microgrid, coordinating distributed energy resources (DERs) for peak demand fulfillment and excess energy utilization. We propose a proportional-integral control system for efficient demand response, achieving reduced post-scheduling costs and a peak-to-average ratio. Comparative analysis reveals Ant Colony Optimization outperforms Binary Particle Swarm Optimization in cost and peak-to-average ratio reduction. Simulations explore two scenarios: Case 1 integrates with the main grid for reliability, while Case 2 utilizes solely renewable energy sources. Although Case 2 exhibits superior performance, Case 1's dependence on the main grid offers greater real-world feasibility. Therefore, Case 1 with optimized DER scheduling emerges as the recommended solution for enhancing microgrid efficiency and ensuring reliable power supply in smart homes.

关键词： Microgrid real-time pricing renewable resources PV systems wind energy systems demand-side management mixed integer linear problem supply-side management chance constrained optimization

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Supply Chain Design Network Model for Biofuel and Petrochemicals from Biowaste 22

Supply Chain Design Network Model for Biofuel and Petrochemi...

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19th International Conference on Process Integration, Modeling and Optimization for Energy Savings and Pollution Reduction (PRES)

作者： Emara, Ismaail A. Gadalla, Mamdouh Ashour, Fatma Cairo Univ Fac Engn Dept Chem Engn Cairo 12654 Egypt British Univ Fac Engn Dept Chem Engn Cairo 11837 Egypt

ISBN: (纸本)9788895608426

Supply Chain (SC) is the effective coordination and integration of all activities performed by several business lines and their infrastructures;such as raw material suppliers, manufacturers, distributors and retailers till delivering the products to the customer. The supply chain facilities location is an important issue which is needed to be solved as it is one of the important pillars in the supply chain design model. Therefore, it is critical for supply chain managing teams and designers to adopt the latest scientific and most effective methods to locate a facility by carrying different scenarios and trade-offs assessment, the used tools are only a decision supporting tools. This paper concentrates on the development status of a decision-support tool for solving supply chain design including location problem of various facilities, using the MILP mixed integer linear problem solving programming model by constructing a generic analytical algorithm to solve this problem. EXECL SOLVER TOOL, MATLAB SOFTWARE with a GUI (graphical user input interface) programmed by the C# (C SHARP) programming software are used. In the MILP programming model iterative algorithm methods are used, where every iteration would generate a whole different new set of solutions to match some constrains, conditions and service levels added by the programmer. The first solution only matches some previous added criteria, resulting in a new set of solutions in the iteration, until finally an optimal solution rises under dynamic environment. In this paper, a typical three layers medium term planning mixed integer linear Programme MILP model for supply chain design is presented and applied for chemicals and biofuel production from rice straw biomass. These three stages are commonly: raw materials collecting areas, distribution center and manufacturing plant locations. With the aid of ASPEN HYSYS simulation software and CAPCOST TOOL, Economic feasibility studies are done for designing supply chain de

关键词： Biodiesel C SHARP Economic feasibility study MATLAB mixed integer linear problem Rice straw Supply chain design model Sustainable development and renewable energy

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Assessment methods for the targeted reconfiguration in distribution networks

Assessment methods for the targeted reconfiguration in distr...

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PowerTech, 2015 IEEE Eindhoven

作者： Toure, S. Vanet, E. Caire, R. Besanger, Y. Univ Grenoble Alpes G2Elab F-38000 Grenoble France CNRS G2Elab F-38000 Grenoble France

ISBN: (纸本)9781479976959

In this paper, we propose methods for minimizing power losses through dynamic reconfiguration. Two methods for determining the best sequence of configurations, while minimizing the total network losses and reconfiguration cost have been developed. The first method is based on a shortest path algorithm, whereas the second one is based on mixed integer linear programming. The algorithms are tested on an IEEE network with and without distributed generation;the results are presented and compared for the two different methods.

关键词： Dynamic Distribution Reconfiguration problem Shortest path algorithm mixed integer linear problem Distributed Generation

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Detailed Modelling of Thermal Units From a Price-Taker's Perspective

Detailed Modelling of Thermal Units From a Price-Taker's Per...

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9th International Conference on the European Energy Market (EEM)

作者： Maenhoudt, Marijn Deconinck, Geert Katholieke Univ Leuven Dept Elect Engn ESAT Div ELECTA Louvain Belgium

ISBN: (纸本)9781467308328;9781467308342

Generation Companies (GenCos) acting as price-takers, schedule their plants according to market price forecasts. As these GenCos do not consider active market price setting as a strategy to increase profits, their performance solely relies on (1) price forecast accuracy and (2) the representation of a plant's operational characteristics. This paper strives at constituting a reference work for thermal plant modelling from a price-taker's perspective. Two main contributions can be distinguished. Firstly it summarizes relevant contributions from literature and merges them into one single, complete formal mixed integer linear problem (MILP) model design. Secondly it adds new features to advance the state-of-the-art and to enhance the applicability of the model in practice. The document is finalised by assessing the model performance by applying it to an exemplary case study.

关键词： thermal unit commitment modelling price-based electricity market mixed integer linear problem price-taker

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