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Models for two- and three-stage two-dimensional cutting stock problems with a limited number of open stacks

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2023年第9期61卷 2894-2915页

作者： Martin, Mateus Yanasse, Horacio Hideki Santos, Maristela O. Morabito, Reinaldo Univ Fed Fluminense Dept Engn Prod Rua Domingos Silverio 135 BR-25650050 Petropolis RJ Brazil Univ Fed Sao Paulo Inst Ciencia & Tecnol Ave Cesare Mansueto Giulio Lattes 1201 BR-12247014 Sao Jose Dos Campos SP Brazil Univ Sao Paulo Inst Ciencias Matemat & Comp Sao Carlos Brazil Univ Fed Sao Carlos Dept Engn Prod Sao Carlos Brazil

We address three variants of the two-dimensional cutting stock problem in which the guillotine cutting of large objects produces a set of demanded items. The characteristics of the variants are the rectangular shape of the objects and items;the number of two or three orthogonal guillotine stages;and a sequencing constraint that limits the number of open stacks to a scalar associated with the number of automatic compartments or available space near the cutting machine. These problems arise in manufacturing environments that seek minimum waste solutions with limited levels of work-in-process. Despite their practical relevance, we are not aware of mathematical models for them. In this paper, we propose an integer linear programming (ILP) formulation for each of these variants based on modelling strategies for the two-dimensional guillotine cutting stock problem and the minimisation of the open stacks problem. The first two variants deal with exact and non-exact 2-stage patterns, and the third with a specific type of 3-stage patterns. Using a general-purpose ILP solver, we performed computational experiments to evaluate these approaches with benchmark instances. The results show that several equivalent solutions of the cutting problem allow obtaining satisfactory solutions with a reduced number of open stacks.

关键词： Cutting stock problems mixed-integer linear programming pattern sequencing integrated problems 2-stage and 3-stage patterns

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Investigation of Electric Vehicles Contributions in an Optimized Peer-to-Peer Energy Trading System

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IEEE ACCESS 2023年 11卷 12489-12503页

作者： Al-Sorour, Ameena Fazeli, Meghdad Monfared, Mohammad Fahmy, Ashraf A. A. Swansea Univ Fac Sci & Engn Dept Elect & Elect Engn Swansea SA1 8EN Wales Swansea Univ ASTUTE Swansea SA1 8EN Wales Helwan Univ Dept Elect Power & Machines Helwan 11795 Egypt

The rapid increase in integration of Electric Vehicles (EVs) and Renewable Energy Sources (RESs) at the consumption level poses many challenges for network operators. Recently, Peer-to-Peer (P2P) energy trading has been considered as an effective approach for managing RESs, EVs, and providing market solutions. This paper investigates the effect of EVs and shiftable loads on P2P energy trading with enhanced Vehicle to Home (V2H) mode, and proposes an optimized Energy Management Systems aimed to reduce the net energy exchange with the grid. mixed-integer linear programming (MILP) is used to find optimal energy scheduling for smart houses in a community. Results show that the V2H mode reduces the overall energy costs of each prosumer by up to 23% compared to operating without V2H mode (i.e., EVs act as a load only). It also reduces the overall energy costs of the community by 15% compared to the houses operating without the V2H mode. Moreover, it reduces the absolute net energy exchanged between the community and the grid by 3%, which enhances the energy independence of the community.

关键词： Batteries Costs State of charge Peer-to-peer computing Vehicle-to-grid Tariffs Electric vehicles mixed integer linear programming Electric vehicle energy management system local consumption mixed-integer linear programming peer-to-peer energy trading

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Risk-averse based optimal operational strategy of grid-connected photovoltaic/wind/battery/diesel hybrid energy system in the electricity/hydrogen markets

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2023年第12期48卷 4631-4648页

作者： Wang, Jun Xu, Xiao Wu, Lan Huang, Qi Chen, Zhe Hu, Weihao Henan Univ Technol Coll Elect Engn Zhengzhou 450001 Peoples R China Sichuan Univ Coll Elect Engn Chengdu 610065 Peoples R China Henan Univ Technol Coll Electromech Engn Zhengzhou 450001 Peoples R China Univ Elect Sci & Technol China Sch Mech & Elect Engn Sichuan Prov Key Lab Power Syst Wide Area Measurem Chengdu 611731 Peoples R China Aalborg Univ Dept Energy Technol Pontoppidanstraede 111 Aalborg Denmark

The techno-economic advantages of grid-connected hybrid energy system (HES) exploit synergies to improve reliability and economic efficiency while maintaining grid stability. Therefore, this paper proposes a risk-averse optimal operational strategy of grid-connected photovoltaic/wind/battery/diesel HES to participate into two energy markets including electricity and hydrogen markets. The grid company can flexibly trade power into two markets to maximally achieve profits based on price arbitrage. The risk influences of the uncertainties, i.e., photovoltaic/wind generation, and electricity prices on the expected revenue are evaluated with CVaR model. For a better exhibition of seasonal variability effects on HES optimal operation strategy, two typical Spring/Summer days are chosen. The proposed risk-averse optimal operational strategy is formulated as a two-stage mixedinteger linear programming (MILP) model. The results in a Spring day simulation under non-risk situation indicate that the overall expected revenue can be improved 2.74 times larger if considering hydrogen market. Moreover, the optimal operational strategy of hydrogen production is considerably affected by unpredictable wind farm. Sensitivity analysis also validates that the changes of PV/WT curtailment penalty have a profound influence than battery degradation coefficient on the HES expected revenue. (c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Risk-averse optimal operational strategy Electricity hydrogen market Hybrid energy system mixed-integer linear programming

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Minimizing recovery cost of network optimization problem

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NETWORKS 2023年第1期81卷 125-151页

作者： Ales, Zacharie Elloumi, Sourour Inst Polytech Paris ENSTA Paris UMA F-91120 Palaiseau France CNAM CEDRIC Paris France

We propose a two-stage recoverable robustness approach that minimizes the recovery cost. In many applications, once the uncertainty xi is revealed, it can be more important to recover a solution x(xi )which is as similar as possible to the nominal solution x(nom) than to minimize the nominal objective value of x(xi). This for example occurs when the nominal solution is implemented on a regular basis or when the uncertainty is revealed late. We define the proactive problem which minimizes the weighted recovery costs over a discrete set of scenarios while ensuring optimality of the nominal objective value of x(nom). We model the recovery cost of a scenario by a distance between the first-stage nominal solution and the second-stage solution recovered for this scenario. We show for two different solution distances d(val) , d(struct) (lama that the proactive problem is NP -hard for both the integer min-cost flow problem with uncertain arc demands and for the integer max-flow problem with uncertain arc capacities. For these two problems, we prove that once uncertainty is revealed, even identifying a reactive solution xr with a minimal distance to a given solution x(nom) is NP-hard for d(struc)(t), and is polynomial for d(val). We highlight the benefits of the proactive approach in a case study on a railroad planning problem. First, we compare it to the anchored and the k-distance approaches. Then, we show the efficiency of the proactive solution over reactive solutions. Finally, we illustrate the recovery cost reduction when relaxing the optimality constraint on the nominal objective of the proactive solution x(nom). We also consider the min-max version of the proactive problem where we minimize the maximal recovery cost over all scenarios. We show that the same complexity results hold for this version. We also exhibit a class of problems for which the set of extreme points of the convex hull of a discrete uncertainty set always contain a worst-case scenario. We show that

关键词： mixed-integer linear programming NP-hardness proactive problem recoverable robustness robust optimization uncertainty modeling

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Bi-objective coordinated production and transportation scheduling problem with sustainability: formulation and solution approaches

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2023年第3期61卷 774-795页

作者： Yagmur, Ece Kesen, Saadettin Erhan Konya Tech Univ Fac Engn & Nat Sci Dept Ind Engn TR-42075 Selcuklu Konya Turkey

This paper studies a new variant of integrated production scheduling and vehicle routing problem where production of customer orders are performed under job-shop environment and order deliveries are made by a heterogeneous fleet of vehicles, each of which is allowed to take multiple trips. Two conflicting objectives are considered, namely minimisation of the total amount of CO2 emitted by the vehicles and minimisation of maximum tardiness resulting from late deliveries. To this end, we present a bi-objective mixed-integer programming formulation. Augmented epsilon-Constraint (Augmecon) method is implemented to find Pareto optimal solutions. Due to problem complexity, Augmecon cannot provide solutions even with small-sized problems. Thus, we adopt Pareto Local Search (PLS) and non-dominated sorting genetic algorithm-II (NSGA-II) for practical sized instances. For small-sized instances involving 5, 6, and 7 customers, experimental results indicate that CPU time of Augmecon are 11, 84, and 524 sec, respectively with an average number of Pareto efficient solution of 3.5. In terms of hypervolume index, Augmecon shows the best performance, followed by NSGA-II with 11.32% and PLS with 20.75% degradation for small-sized instances. For medium and large-sized instances, PLS shows worse performance than NSGA-II by 16.87% and 40.48%.

关键词： Vehicle routing problem job shop scheduling mixed-integer linear programming sustainability NSGA-II multi-objective optimisation

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A decomposition approach for the periodic consistent vehicle routeing problem with an application in the cleaning sector

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2023年第22期61卷 7727-7748页

作者： Messaoudi, Bilal Oulamara, Ammar Salhi, Said Univ Lorraine LORIA Lab Campus Sci BP 239 F-54506 Vandoeuvre Les Nancy France Antsway SA ARTEM 92 Rue Sergent Blandan F-54000 Nancy France Univ Kent Kent Business Sch Ctr Logist & Heurist Optimisat CLHO Canterbury CT2 7FS Kent England

This study is inspired by a challenging logistic problem encountered in the cleaning service sector. The company wishes to solve the consistent vehicle routeing problem over a three-month planning horizon. The company has a heterogeneous vehicle fleet to guarantee multiple frequencies of visits to its customers. The objective is to minimise the number of vehicles used and the total distance travelled. This problem is a generalisation of the periodic vehicle routeing problem. We decompose the problem into two sub-problems, namely, the planning and routeing optimisation sub-problems. We construct a mathematical model for the former and a large neighbourhood search for the latter. We evaluate the performance of our approach using the results of the industrial partner and instances from the literature on problems that are closely related to our case study. Our approach is found to be effective and robust. Our results outperform the existing company's plan in terms of solution quality, and staff convenience, and speed. We also discovered new best solutions on some of the instances from the literature.

关键词： Routing driver consistency mixed-integer linear programming large neighbourhood search Decomposition methods

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Coordinated Voltage Control of Microgrids With Integrated Electric Vehicles in Real-World Experiment and Application: Industrial Design and Implementation on EUREF-Campus in Berlin

IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN INDUSTRIAL E...

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IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN INDUSTRIAL ELECTRONICS 2024年第2期5卷 359-368页

作者： Chen, Jiawen Popova, Raisa Raab, Andreas F. Graute, Hannah Rojas, Mauricio Strunz, Kai Tech Univ Berlin Chair Sustainable Elect Networks & Sources Energy Dept Elect Engn & Comp Sci D-10587 Berlin Germany Deutsch Bahn Energie D-10318 Berlin Germany Schneider Elect D-10829 Berlin Germany

A coordinated voltage control algorithm is developed to facilitate the integration of electric vehicles into microgrids. This proposed algorithm reduces the voltage fluctuations via the optimal adjustment of the tap positions of on-load tap changers and of the reactive power injections of inverter-based distributed energy resources. Based on the proposed voltage control algorithm, an industrial implementation framework is established to enable the interactive communications among the on-load tap changers, the inverter-based distributed energy resources, etc. Compared to previous studies on voltage regulation in microgrids, this work is distinguished by the fact that the proposed voltage control algorithm is implemented and tested on a real-world experimental test site, known as the micro smart grid on the EUREF-Campus in Berlin. Constraints, such as actual process latencies are readily observed. The micro smart grid comprises a power transformer with on-load tap changer, rooftop photovoltaic systems, battery energy storage systems, and electric vehicle charging stations. The real-world test results confirm that the voltage deviations are significantly reduced by the coordinated voltage control algorithm, as opposed to the uncontrolled state. Thanks to the analysis of the trigger cycle of the proposed algorithm, the lifetime of the on-load tap changer can be extended while ensuring the effectiveness of voltage control.

关键词： Voltage control Reactive power Sensitivity On load tap changers Industrial electronics Electric vehicles Smart grids Active network management distributed energy resource electric vehicle microgrid mixed-integer linear programming on-load tap changer optimization photovoltaic systems renewable energy voltage control

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Offering strategy of a price-maker virtual power plant in the day- ahead market

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INTERNATIONAL JOURNAL OF RENEWABLE ENERGY DEVELOPMENT-IJRED 2023年第4期12卷 666-+页

作者： Nguyen-Hong, Nhung Quang, Khai Bui Thanh, Long Phan Vo Huynh, Duc Bui Hanoi Univ Sci & Technol Sch Elect & Elect Engn Dept Elect Engn Hanoi Vietnam

With the rapid increase of renewable energy sources (RESs), the virtual power plant model (VPP) has been developed to integrate RESs, energy storage systems (ESSs), and local customers to overcome the RESs' disadvantages. When the VPP's capacity is large enough, it can participate in the electricity market as a price-maker instead of a price-taker to obtain a higher profit. This study proposes a bi-level optimization model to determine the optimal trading strategies of a price-maker VPP in the day-ahead (DA) market. The operation schedule of the components in the VPP is also optimized to achieve the highest profit for the VPP. In the bi-level optimization problem, the upper-level model is maximizing the VPP's profit while the lower-level model is the DA market-clearing problem. The bi-level optimization problem is formulated as a Mathematical Problem with Equilibrium Constraints (MPEC), reformulated to a mixed integer linear Problem (MILP), then solved by GAMS and CPLEX. This study applies the bi-level optimization model to a test VPP system, including wind plants (WP), solar plants (PV), biogas energy plants (BG), ESSs, and several customers. The maximum power outputs of WP and PV are 100MW and 90MW, respectively. The total installed capacity of BG is 70MW, while the ESS' rated capacity is 100MWh. The local customers have the highest total consumption of 100MW. In addition to the VPP, four GENCOs and three retailers participate in the DA market. The results show that the market-clearing price varies depending on the participants' production/consumption quantity and offering/bidding price. However, based on the optimization model, the VPP can take full advantage of WP and PV available power output, choose the right time to operate BG, then obtain the highest profit. The results also show that with the ESS' rated capacity of 100MWh, the ESS' rated discharging/charging power increased from 10MW to 50MW will increase VPP's profit from 45987$ to 49464$. The obtained res

关键词： Day-ahead market mathematical problem with equilibrium constraints mixed-integer linear programming price-maker renewable energy virtual power plants

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Learning-Assisted Variables Reduction Method for Large-Scale MILP Unit Commitment

IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY

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IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY 2023年 10卷 245-258页

作者： Shekeew, Mohamed Ibrahim Abdelaziz Venkatesh, Bala Toronto Metropolitan Univ Dept Elect Comp & Biomed Engn Toronto ON M5B 2K3 Canada

The security-constrained unit commitment (SCUC) challenge is solved repeatedly several times every day, for operations in a limited time. Typical mixed-integer linear programming (MILP) formulations are intertemporal in nature and have complex and discrete solution spaces that exponentially increase with system size. Improvements in the SCUC formulation and/or solution method that yield a faster solution hold immense economic value, as less time can be spent finding the best-known solution. Most machine learning (ML) methods in the literature either provide a warm start or convert the MILP-SCUC formulation to a continuous formulation, possibly leading to sub-optimality and/or infeasibility. In this paper, we propose a novel ML-based variables reduction method that accurately determines the optimal schedule for a subset of trusted generators, shrinking the MILP-SCUC formulation and dramatically reducing the search space. ML indicators sets are created to shrink the MILP-SCUC model, leading to improvement in the solution quality. Test results on IEEE systems with 14, 118, and 300 busses, the Ontario system, and Polish systems with 2383 and 3012 busses report significant reductions in solution times in the range of 48% to 98%. This is a promising tool for system operators to solve the MILP-SCUC with a lower optimality gap in a limited-time operation, leading to economic benefits.

关键词： Generators Power systems Costs Spinning Machine learning programming Power transmission lines mixed-integer linear programming UC variables reduction unit commitment

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A linear programming based method for designing menus for controlled feeding trials

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AMERICAN JOURNAL OF CLINICAL NUTRITION 2023年第2期117卷 408-413页

作者： Gerdessen, Johanna C. Borgonjen-van den Berg, Karin J. Wageningen Univ Grp Operat Res & Logist Hollandseweg 1 NL-6706 KN Wageningen Netherlands Wageningen Univ Div Human Nutr & Hlth Stippeneng 4 NL-6708 WE Wageningen Netherlands

Background: Controlled feeding trials are an important method to determine cause-effect relationships between dietary intake and metabolic parameters, risk factors, or health outcomes. Participants of a controlled feeding trial receive full-day menus during a prespecified period of time. The menus have to comply with the nutritional and operational standards of the trial. Levels of nutrients under investigation should differ sufficiently between intervention groups, and be as similar as possible for all energy levels within intervention groups. Levels of other key nutrients should be as similar as possible for all participants. All menus have to be varied and manageable. Designing these menus is both a nutritional and a computational challenge that relies largely on the expertise of the research dietician. The process is very time consuming, and last-minute disruptions are very hard to ***: This paper demonstrates a mixed integer linear programming model to support the design of menus for controlled feeding ***: The model is demonstrated for a trial that involved consumption of individualized, isoenergetic menus with either a low or a high protein ***: All menus generated by the model comply with all standards of the trial. The model allows for including tight ranges on nutrient composition, and complex design features. The model is very helpful in managing contrast and similarity of key nutrient intake levels between groups and energy levels, and in coping with many energy levels and nutrients. The model helps to propose several alternative menus and to manage last-minute disruptions. The model is flexible;it can easily be adapted to suit trials with other components or different nutritional ***: The model helps to design menus in a fast, objective, transparent, and reproducible way. It greatly facilitates the design procedure for menus in controlled feeding trials and lowers development costs.

关键词： mixed-integer linear programming optimization linearization fully controlled dietary intervention operations research

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