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Multi-stage stochastic wind-thermal generation expansion planning with probabilistic reliability criteria

IET GENERATION TRANSMISSION & DISTRIBUTION 2022年第3期16卷 517-534页

作者： Wang, Qi Luo, Xianjue Ma, Honglian Gong, Naiwei Xi An Jiao Tong Univ Sch Elect Engn Xian 710049 Shaanxi Peoples R China Global Energy Interconnect Dev & Cooperat Org Beijing Peoples R China

Due to the growing proportion of uncertain and fluctuating renewable energy sources in the power system, reasonable generation expansion considering the uncertainties is desperately needed. This paper proposes a novel three-stage wind-thermal generation expansion planning model based on representative day unit commitment that incorporates the uncertainty of wind power and load and the probabilistic reliability criteria. The probabilistic reliability criteria are considered by simulating random outage events of thermal units using a robust approach. The consequent robust reliability model is reformulated as mixed-integer linear programming models and integrated into the multi-stage generation expansion planning model. A decomposed strategy based on the Benders decomposition is adopted to tackle with the large-scale original model. Case studies are performed on both the revised IEEE 14-bus and IEEE 118-bus test systems to validate the effectiveness of proposed model and method. Numerical results show that the proposed generation planning method balances the economy and reliability of the system.

关键词： wind power three-stage wind-thermal generation expansion planning model consequent robust reliability model wind power plants large-scale original model power system power generation dispatch linear programming integer programming generation planning method mixed-integer linear programming models power generation economics Benders decomposition IEEE 118-bus test systems representative day unit commitment fluctuating renewable energy sources probability thermal power stations IEEE 14-bus test systems stochastic processes reasonable generation expansion thermal units power generation scheduling multistage stochastic wind-thermal generation expansion planning power generation planning probabilistic reliability criteria uncertain energy sources multistage generation expansion planning model power generation reliability

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Location of cross-docking centers and vehicle routing scheduling under uncertainty: A fuzzy possibilistic-stochastic programming model

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APPLIED MATHEMATICAL MODELLING 2014年第7-8期38卷 2249-2264页

作者： Mousavi, S. Meysam Vandani, Behnam Tavakkoli-Moghaddam, R. Hashemi, H. Shahed Univ Fac Engn Dept Ind Engn Tehran Iran Islamic Azad Univ Qazvin Branch Fac Ind & Mech Engn Qazvin Iran Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Islamic Azad Univ South Tehran Branch Young Researchers & Elite Club Tehran Iran

The location of multiple cross-docking centers (CDCs) and vehicle routing scheduling are two crucial choices to be made in strategic/tactical and operational decision levels for logistics companies. The choices lead to more realistic problem under uncertainty by covering the decision levels in cross-docking distribution networks. This paper introduces two novel deterministic mixed-integer linear programming (MILP) models that are integrated for the location of CDCs and the scheduling of vehicle routing problem with multiple CDCs. Moreover, this paper proposes a hybrid fuzzy possibilistic-stochastic programming solution approach in attempting to incorporate two kinds of uncertainties into mathematical programming models. The proposed solving approach can explicitly tackle uncertainties and complexities by transforming the mathematical model with uncertain information into a deterministic model. m' imprecise constraints are converted into 2Rm' precise inclusive constraints that agree with R alpha-cut levels, along with the concept of feasibility degree in the objective functions based on expected interval and expected value of fuzzy numbers. Finally, several test problems are generated to appraise the applicability and suitability of the proposed new two-phase MILP model that is solved by the developed hybrid solution approach involving a variety of uncertainties and complexities. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Distribution networks Cross-docking centers location Vehicle routing scheduling Fuzzy possibilistic programming Stochastic programming mixed-integer linear programming models

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Stochastic economic dispatch of power system with multiple wind farms and pumped-storage hydro stations using approximate dynamic programming

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IET RENEWABLE POWER GENERATION 2020年第13期14卷 2507-2516页

作者： Lin, Shunjiang Fan, Guansheng Jian, Ganyang Liu, Mingbo South China Univ Technol Sch Elect Power Engn Guangzhou 510640 Peoples R China China Southern Power Grid Elect Power Res Inst Guangzhou 510663 Peoples R China

The stochastic economic dispatch problem of power system with multiple wind farms and pumped-storage hydro stations is formulated as a specific stochastic dynamic programming (DP) model, i.e. stochastic storage model, it is impossible to obtain an accurate solution due to the curse of dimensionality. Based on the approximate DP (ADP) method, the stochastic storage model can be transformed into a series of mixed-integer linear programming (MILP) models by describing the approximate value functions (AVFs) as convex piecewise linear functions in post-decision states. The AVFs are first initialised using the results of the deterministic model under a forecast scenario of wind farm output and then trained by scanning stochastic sampling scenarios consecutively with the successive projective approximation routine algorithm. To obtain a near-optimal day-ahead dispatch scheme, the forecast scenario is substituted into the MILP models expressed by the trained AVFs and is solved forward through each time interval. The network constraints are incorporated by the while-loop detection of critical lines. Test results on an actual provincial power system and the modified IEEE 39-bus system, including the comparison among the ADP, DP, scenario-based and chance-constrained programming methods, demonstrate the feasibility and efficiency of the proposed model and algorithm.

关键词： approximation theory stochastic processes dynamic programming power generation economics wind power plants power generation dispatch pumped-storage power stations integer programming stochastic programming power system security optimisation linear programming multiple wind farms pumped-storage hydro stations approximate dynamic programming stochastic economic dispatch problem specific stochastic dynamic programming model stochastic storage model approximate DP method mixed-integer linear programming models approximate value functions AVFs convex piecewise linear functions deterministic model forecast scenario wind farm output stochastic sampling scenarios successive projective approximation routine algorithm near-optimal day-ahead dispatch scheme MILP models actual provincial power system modified IEEE 39-bus system

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A top-down cutting approach for modeling the constrained two- and three-dimensional guillotine cutting problems

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2021年第12期72卷 2755-2769页

作者： Martin, Mateus Morabito, Reinaldo Munari, Pedro Univ Fed Sao Paulo Sao Paulo Brazil Univ Fed Sao Carlos Sao Carlos Brazil

In this article, we address the Constrained Two-dimensional Guillotine Cutting Problem (C2GCP) and the Constrained Three-dimensional Guillotine Cutting Problem (C3GCP). These problems consist of cutting a rectangular two-/three-dimensional object with orthogonal guillotine cuts to produce ordered rectangular two-/three-dimensional items seeking the most valuable subset of items cut. They often appear in manufacturing settings that cut objects to produce item types of low demand, such as in the cutting of flat glass in the glass industry, rocks in the granite and marble industries and steel blocks in the metallurgical industry. To model and solve these problems, we propose a novel top-down cutting approach that leads to effective mixed integer linear programming models for the C2GCP and the C3GCP. The insight of the proposed approach is to represent the cutting pattern as a binary tree, in which the root node is the object, and branches correspond to guillotine cuts. The results of computational experiments with a general-purpose optimization solver and using three sets of benchmark instances showed that the proposed models are competitive with state-of-the-art formulations of the C2GCP and the C3GCP in quality of solution and processing times, particularly when the number of items in an optimal solution is moderate.

关键词： Cutting and packing 2D and 3D guillotine cutting non-staged patterns mixed-integer linear programming models top-down cutting

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Risk-aware last-minute data backup in inter-datacenter networks

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IET NETWORKS 2019年第5期8卷 307-320页

作者： Das, Shrayan Panda, Kirtan Gopal Sen, Debarati Arif, Wasim Indian Inst Technol GS Sanyal Sch Telecommun Kharagpur W Bengal India Natl Inst Technol Dept Elect & Commun Engn Silchar India

Network failure caused by disasters (both natural and man-made like earthquakes, floods, cyclones, electromagnetic pulse attacks etc.) result in communication disruption and huge amounts of data loss in the backbone datacenter (DC) networks. To prevent such large-scale network disruptions and quickly resume connectivity after the disaster, network operators require improved and efficient data-transfer algorithms in geographically distributed (geo-distributed) optical inter-DC networks. Minimising loss of infrastructure and preventing network disruption requires estimating the damage from a possible disaster. In this study, the authors consider a mutual backup model, where DCs can serve as backup sites of each other, thereby significantly reducing the backup duration (i.e. DC-Backup-Window (DC-B-Wnd)). They specifically consider the joint optimisation of probabilistic backup site selection and the amount of data to be backed up. They propose mixed-integer linear programming models for backup time minimisation using a single DC as well as dual DCs at backup sites. Further, they investigate the trade-off between DC-B-Wnd and the computational complexity of the proposed algorithms and perform extensive numerical simulations to show that, in the case of disasters, single and dual DC backups with risk-aware probabilistic path selection give shorter backup windows as compared to existing algorithms.

关键词： linear programming integer programming computer centres computer networks computer network reliability minimisation probability communication complexity numerical analysis communication disruption backbone datacenter networks large-scale network disruptions data-transfer algorithms mutual backup model DC-B-Wnd probabilistic backup site selection mixed-integer linear programming models backup time minimisation single DC backups dual DC backups risk-aware probabilistic path selection interdatacenter networks risk-aware last-minute data backup electromagnetic pulse attacks optical interDC networks network disruption prevention DC-backup-window optimisation numerical simulations computational complexity

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Research on Data- driven Enterprise Raw Material Ordering and Optimal Transportation Scheme

Research on Data- driven Enterprise Raw Material Ordering an...

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Asia Conference on Algorithms, Computing and Machine Learning (CACML))

作者： Mi, Kerun Gu, Hai Liu, Jiacheng Yang, Liu Xiangtan Univ Sch Math & Computat Sci Xiangtan Peoples R China Xiangtan Univ Hunan Key Lab Computat & Simulat Sci & Engn Xiangtan Peoples R China

ISBN: (数字)9781665482905

ISBN: (纸本)9781665482905

Ordering and transportation optimization of raw material is a classic problem in the field of optimization. Based on the analysis, evaluation and prediction of previous data, this paper fully considers the actual situation of ordering, transshipment and storage, and establishes a multistage and large-scale mixed integer linear programming model for ordering and transporting raw materials. Combined with extensive data background, select appropriate indicators, and establish supplier evaluation systems by using entropy weightCRITIC and RTOPSIS method. GM ( 1,1) is used to predict the general trend, the ARIMA model is used to predict the random fluctuation items, and a grey time series prediction model is constructed to obtain the predicted values of the data of the supply and loss rate in the next cycle. The prediction result are introduced into the planning model as parameters, and the evaluation score are used to construct a satisfaction function. The final goal of mixed integer linear programming model, as well as the three goals of sorting, transferring and storing, are obtained by reduction process. Finally, this paper uses Gurobi to solve practical problems, and obtains the ordering scheme and transshipment scheme that are superior to the historical schemes in ordering cost, transshipment loss and storage cost

关键词： Supply and demand ordering decisions Supplier evaluation Grey time series prediction mixed-integer linear programming models Gurobi

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An efficiency and robustness analysis of warm-start mathematical models for idle and waiting times optimization in the flow shop

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年第0期166卷 107976-107976页

作者： De Abreu, Alex Paranahyba Fuchigami, Helio Yochiro Univ Fed Goias Fac Sci & Technol Goiania Go Brazil Univ Fed Sao Carlos Dept Prod Engn Sao Carlos SP Brazil

This paper aims to address current manufacturing problems such as high buffers and energy waste by considering a novel performance measure, the sum of the core and front idle time of each machine and the core waiting time of each job, within the permutation flow shop scheduling optimization. Four new mixed-integer linear programming (MILP) models and three warm-start procedures were implemented in 240 instances of a widely used benchmark. The results of computational experiments were evaluated using performance profiles, considering computing times and optimality gaps. Among the models, the solver achieved better results with the position based models than with the sequence-based models, achieving 25% more optimal solutions, being more efficient and robust. Regarding the warm-start strategies, we highlight the procedure with the longest processing time (LPT) heuristic as the best method among the seven studied.

关键词： Flow shop scheduling Idle time optimization Waiting time optimization mixed-integer linear programming models Heuristics Warm-start

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Three-dimensional guillotine cutting problems with constrained patterns: MILP formulations and a bottom-up algorithm

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EXPERT SYSTEMS WITH APPLICATIONS 2021年 168卷 114257-114257页

作者： Martin, Mateus Oliveira, Jose Fernando Silva, Elsa Morabito, Reinaldo Munari, Pedro Univ Fed Sao Carlos Dept Prod Engn Sao Carlos Brazil INESC TEC Porto Portugal Univ Porto Fac Engn Porto Portugal

In this paper, we address the Constrained Three-dimensional Guillotine Cutting Problem (C3GCP), which consists of cutting a larger cuboid block (object) to produce a limited number of smaller cuboid pieces (items) using orthogonal guillotine cuts only. This way, all cuts must be parallel to the object's walls and generate two cuboid sub-blocks, and there is a maximum number of copies that can be manufactured for each item type. The C3GCP arises in industrial manufacturing settings, such as the cutting of steel and foam for mattresses. To model this problem, we propose a new compact mixed-integer non-linear programming (MINLP) formulation by extending its two-dimensional version, and develop a mixed-integer linear programming (MILP) version. We also propose a new model for a particular case of the problem which considers 3-staged patterns. As a solution method, we extend the algorithm of Wang (1983) to the three-dimensional case. We emphasise that the C3GCP is different from 3D packing problems, namely from the Container Loading Problem, because of the guillotine cut constraints. All proposed approaches are evaluated through computational experiments using benchmark instances. The results show that the approaches are effective on different types of instances, mainly when the maximum number of copies per item type is small, a situation typically encountered in practical settings with low demand for each item type. These approaches can be easily embedded into existing expert systems for supporting the decision-making process.

关键词： Cutting and packing Constrained three-dimensional cutting Non-staged and 3-staged patterns mixed-integer linear programming models Bottom-up packing

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