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Star discrepancy subset selection: Problem formulation and efficient approaches for low dimensions

JOURNAL OF COMPLEXITY 2022年 70卷

作者： Clement, Francois Doerr, Carola Paquete, Luis Sorbonne Univ LIP6 CNRS Paris France Univ Coimbra Dept Informat Engn CISUC Coimbra Portugal

Motivated by applications in instance selection, we introduce the star discrepancy subset selection problem, which consists of finding a subset of mout of npoints that minimizes the star discrepancy. First, we show that this problem is NP-hard. Then, we introduce a mixed integer linear formulation (MILP) and a combinatorial branch-and-bound (BB) algorithm for the star discrepancy subset selection problem and we evaluate both approaches against random subset selection and a greedy construction on different use-cases in dimension two and three. Our results show that the MILP and BB are efficient in dimension two for large and small m/nratio, respectively, and for not too large n. However, the performance of both approaches decays strongly for larger dimensions and set sizes. As a side effect of our empirical comparisons we obtain point sets of discrepancy values that are much smaller than those of common low-discrepancy sequences, random point sets, and of Latin Hypercube Sampling. This suggests that subset selection could be an interesting approach for generating point sets of small discrepancy value. (C) 2022 Elsevier Inc. All rights reserved.

关键词： Computational geometry Discrepancy Subset selection mixed-integer linear programming Branch and bound

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Optimal scheduling of modernization measures for typical non-residential buildings

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ENERGY 2022年第PartA期238卷 121871-121871页

作者： Richarz, Jan Henn, Sarah Osterhage, Tanja Muller, Dirk Rhein Westfal TH Aachen EON Energy Res Ctr Inst Energy Efficient Bldg & Indoor Climate Mathieustr 10 D-52074 Aachen Germany

Existing non-residential buildings account for a significant proportion of the energy consumption of the European building stock. Modernizing these buildings can significantly contribute to declared emission reduction targets. Modernization measures are rarely realized in the life cycle of buildings but have longterm effects on their energetic performance. Therefore, it is not only essential to identify future-oriented modernization measures but also to schedule them over the life cycle of a building. For this purpose, we present a mixed-integer linear program that schedules measures for a building energy system including envelope and supply system. The program determines not only the optimal combination of modernization measures but also the respective optimal point of time when each measure shall be realized. A multi-objective optimization is conducted to minimize carbon emissions and net present value. Thermal demand profiles serve as input for the optimization model and are calculated preliminary using dynamic simulations. Constraints and boundary conditions are specified separately for each prospective year of the schedule's time horizon. Results showed that the constitution of a building energy system changes several times throughout a schedule. Determined Pareto-efficient solutions reveal that carbon emissions could be saved more cost-efficiently than with approaches without scheduling. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Building energy system Modernization schedule mixed-integer linear programming Multi-objective Optimization

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Shrinking and receding horizon approaches for long-term operational planning of energy storage and supply systems

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ENERGY 2022年第PartD期239卷 122066-122066页

作者： Wakui, Tetsuya Akai, Kazuki Yokoyama, Ryohei Osaka Prefecture Univ Dept Mech Engn Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan

To efficiently solve long-term operational planning problems of energy storage and supply systems, a near-optimal solution method based on the shrinking and receding horizon approaches was developed. A lower bound of the original problem is first calculated by solving a simplified problem, in which the number of binary variables is reduced and the related constraints are simplified. Then, a short-term operational planning problem, with a shrunken planning horizon length, is solved by providing the simplified problem results as the terminal condition for stored energy. Within this problem, the original binary variables and constraints are considered. The short-term operational planning is updated using a receding horizon approach, in which the initial and terminal conditions are provided by the previous short-term operational planning results and simplified problem results, respectively. The solution, obtained by connecting the solutions in all the updating horizons, is regarded as a near-optimal solution of the original problem. The developed method was applied to solve a long-term operational planning problem for an energy storage and supply system, which includes a photovoltaic unit and a metal hydride tank with a water electrolyzer. The results showed that the developed method could find a better solution in a shorter computation time than the conventional methods. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Long-term energy storage planning Two-stage optimization Receding horizon approach mixed-integer linear programming Hydrogen storage

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A hierarchical capacitated facility location-allocation model for planning maternal healthcare facilities in India

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年 167卷

作者： Chouksey, Ankit Agrawal, Anil Kumar N. Tanksale, Ajinkya Indian Inst Technol BHU Varanasi Dept Mech Engn Varanasi 221005 Uttar Pradesh India

The present work on maternal healthcare in India is motivated by its current status emerging out of limited availability and accessibility of related facilities. Planning for the required maternal healthcare facilities, from basic ones to neonatal ones, is a tedious task from the financial perspectives of both users and the government. This problem has been addressed by proposing a mixed-integer linear programming formulation for determining the optimal number and location of these capacitated and varied facilities and also for the allocation of mothers-to-be to these facilities while minimizing the overall cost. Suitable additional valid inequalities are proposed to be incorporated into the NP-hard model for reducing the computational burden. For further computational advantage, a sequential approach is also proposed. Comparative performance of the proposed approaches has been analyzed using several problems with wide variation in the problem parameters' values. The sequential approach is found to be very effective and computationally efficient. The results of the sensitivity analyses with respect to coverage distance, capacity, referral proportion and fixed cost provide important and practical insights related to the mix of the facilities to be established. The application of the model for a district in India proves the suitability of the model in the Indian context.

关键词： Operations research in healthcare Maternal healthcare Facility location and allocation mixed-integer linear programming Problem decomposition Valid inequalities

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A sequentially preventive model enhancing power system resilience against extreme-weather-triggered failures

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2022年 156卷 111945-111945页

作者： Liu, Hanchen Wang, Chong Ju, Ping Li, Hongyu Hohai Univ Coll Energy & Elect Engn Nanjing 211100 Peoples R China

ABS TRACT Affected by climate change, extreme weather events are occurring with increasing frequency and severity, resulting in more and more blackouts. Thus, resilience enhancement is drawing wider attention from academia and industry. Nevertheless, most of the existing studies ignore the resilience enhancement operational strategies against the extreme-weather-triggered cascading failures. To solve these problems, this paper proposes a sequentially proactive operational strategy to enhance resilience against extreme-weather-triggered cascading failures. Firstly, due to the difference between the time scales of extreme weather events and cascading failures, the outage process under extreme weather conditions is regarded as a double-time-dimension process, including the weather disaster and cascading failures. Besides, given that extreme weather and cascading failures are random, the random scenarios sampling method is utilized to simulate the double-time-dimension outage pro-cess. Further, customized double-time-dimension process constraints are introduced to the proposed model to represent the correlation between extreme weather events and cascading outages. Meanwhile, by regarding the probability of outages scenarios as the weight of each objective, the proposed model can be transformed into mixed-integer linear programming. Numerical studies validate the feasibility and effectiveness of the proposed method. The results demonstrate that the proposed strategies can prevent extreme weather from triggering cascading failures and reduce the size of blackouts, to enhance the resilience performance of the power system. The findings can provide some meaningful insights for system operators to adopt resilience enhancement measures against the extreme-weather-triggered cascading failures.

关键词： Cascading failure Double-time-dimension-outage process Extreme weather events Power system resilience mixed-integer linear programming

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On the characterization and evaluation of residential on-site E-car-sharing

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ENERGY 2022年 246卷 123400-123400页

作者： Corinaldesi, Carlo Lettner, Georg Auer, Hans Vienna Univ Technol Energy Econ Grp EEG Gusshausstr 25-29E370-3 A-1040 Vienna Austria

E-car-sharing concepts can play a key role in future urban areas as a new and sustainable transport system. When it comes to residential buildings, the added values of sharing systems are reduced parking space and increased use of solar photovoltaics generation on-site. This work proposes a simple and complete method to define residential building tenants' optimal investment and operation, switching from car ownership to an e-car-sharing system. A mixed-integer linear optimization framework describes technologies such as battery storages, solar photovoltaics, electric vehicles, and charging stations. Furthermore, different scenarios are defined and simulated in order to investigate and evaluate the economic potential of residential on-site e-car-sharing. It is shown that with the actual grid tariff design in Austria, the integration of bidirectional charging stations is not cost-effective if considering only the Day-Ahead spot market. The results show that integrating an e-car-sharing system in a residential building allows for fewer cars and charging stations with higher nominal power, reducing the annual total costs of the residential building tenants by up to 29%. On the other hand, the results indicate that e car-sharing systems can also lead to lower optimal installed solar photovoltaic power.(c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Electric Vehicle E-Car-sharing systems Energy modeling Investment mixed-integer linear programming Energy management Photovoltaic Battery storage

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Metaheuristics for multiobjective optimization in energy-efficient job shops

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2022年第0期115卷

作者： Gonzalez, Miguel A. Rasconi, Riccardo Oddi, Angelo Univ Oviedo Dept Comp Oviedo Spain ISTC CNR Inst Cognit Sci & Technol Rome Italy

Energy awareness is one of the most relevant research directions in scheduling problems. In this paper we consider the minimization of both the makespan and the energy consumption in the classical job shop scheduling problem. The energy model considered allows several possible states for the machines: off, stand-by, idle, setup and processing. To solve this multi-objective problem we propose an NSGA-II based evolutionary algorithm combined with local search and a heuristic procedure to improve the energy consumption of a given schedule. We also propose an advanced constraint programming (CP) approach as well as a mixed-integer linear programming (MILP) model, to the aim of comparing their performances against those obtained with the NSGA-II. The experimental study is performed against a benchmark set that extends by 41 instances of increasing size, the set tackled in the previous literature against the same problem. The experiments demonstrate the superiority of the NSGA-II algorithm over all other methods, despite the utilization of CP and MILP allows to draw interesting conclusions on the overall solution optimality, revealing that there is still room for further optimization.

关键词： Evolutionary algorithms Heuristic search Constraint programming mixed-integer linear programming Job-shop scheduling Energy aware scheduling

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Assigning and sequencing storage locations under a two level storage policy: Optimization model and matheuristic approaches x2729

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2022年 108卷 102565-102565页

作者： Lanza, Giacomo Passacantando, Mauro Scutella, Maria Grazia Univ Pisa Dept Comp Sci Largo Bruno Pontecorvo 3 I-56127 Pisa Italy

We deal with a problem which combines storage location assignment with sequencing decisions about the assigned storage locations. Given a set of different product types, with the corresponding storage demand, a set of capacitated storage locations has to be assigned to each product type for the corresponding storing operations. In addition, a suitable sequencing of the assigned storage locations must be devised for each product type, i.e., it has to be decided the ordering with which the storage locations will be filled up during the storing operations. A motivation is that a First-In First-Out (FIFO) picking criterion among storage locations is required per product type. The sequencing established for the assigned storage locations will therefore allow to easily implement the FIFO policy in the successive order picking. Moreover, the selected sequencing also determines the availability of extra storage per product type, on top of pairs of consecutive storage locations along the sequence. The goal is to maximize the storage capacity which remains available after the assignment of the storage locations. We prove the NP-Hardness of the problem and we model it as a constrained multicommodity flow problem on an auxiliary graph. We then propose a mixed-integer linear programming (MILP) model, with some valid inequalities, based on the multicommodity flow formulation. Two relaxations are proposed as well to estimate the quality of the model solutions. Two matheuristic approaches are then designed starting from the MILP model. The proposed methodology is applied to a case study related to a large warehouse with a high stock rotation index in tissue logistics, which motivated our study. Computational results on a wide test bed related to such a real application context show the efficiency and the efficacy of the presented approaches.(c) 2021 Elsevier Ltd. All rights reserved.

关键词： Storage location assignment Storage location sequencing mixed-integer linear programming Multicommodity flows Matheuristic

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Parametric optimization-based peer-to-peer energy trading among commercial buildings considering multiple energy conversion

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APPLIED ENERGY 2022年第PartB期306卷 118040-118040页

作者： Zhang, Heng Zhang, Shenxi Hu, Xiao Cheng, Haozhong Gu, Qingfa Du, Mengke Shanghai Jiao Tong Univ Key Lab Control Power Transmission & Convers Minist Educ Shanghai 200240 Peoples R China Northeast Elect Power Univ Jilin Jilin Peoples R China State Grid Henan Elect Power Res Inst Zhengzhou Peoples R China State Grid Chaoyang Elect Supply Co Chaoyang Peoples R China

A peer-to-peer energy trading framework of buildings considering multi-energy coupling is presented in this study to improve energy efficiency and achieve cost savings. Microsources, such as photovoltaic and microcombined heat and power, are used to meet electricity and heating demands, while the problem of unbalanced power is solved via the main grid and other peers through peer-to-peer energy trading. All peers aim to maximize their revenue and create trading strategies (i.e., trading period and volume) based on the time-of-use tariff released by the main grid. The trading model established by each peer is a parametric optimization-based problem because each peer must consider the trading willingness of other peers when formulating strategies. A new mixed-integer linear programming problem to maximize total profit can be finally formulated to obtain an equilibrium solution that satisfies all peers. Results show that the proposed peer-to-peer transaction approach can reduce energy bills of buildings. Daily purchased electricity from the main grid decreases by 8.9% through peerto-peer energy trading between different buildings. In addition, compared with the building peer-to-peer transaction that only considers electricity energy management, the amount of purchased electricity from the main network can be reduced by 4.2% a day when multi-energy coupling is considered in peer-to-peer.

关键词： Peer-to-peer Buildings Multi-energy copuling mixed-integer linear programming Parametric optimization

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Model-predictive energy management system for thermal batch production processes using online load prediction

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COMPUTERS & CHEMICAL ENGINEERING 2022年 163卷

作者： Fuhrmann, Florian Schirrer, Alexander Kozek, Martin Tech Univ Wien Inst Mech & Mechatron Getreidemarkt 9-BA A-1060 Vienna Austria

Predictive energy management systems (EMS) enable industrial plants to participate in the modern power market and reduce energy cost. In this paper, a novel modular model predictive EMS specifically designed for industrial thermal batch processes is presented. The EMS consists of a two-layer mixed-integer model predictive controller and an online load predictor, and thus solves the main challenges of EMS in industry - high implementation costs and the possible reduction of production reliability. The modular formulation of the optimization problem enables system integrators to implement the EMS without time-consuming modelling tasks and elaborate parameter tuning. The online load predictor estimates the typical pulse-like heat loads of batch processes ensuring both - reliable production and maximal flexibility of the power demand. The utilization of real-time data provides additional robustness against uncertainties caused by human operators. The performance of the EMS is evaluated in a case study of an existing food plant. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )

关键词： Energy management system Model predictive control Online load prediction mixed-integer linear programming Thermal batch processes

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