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Quantum computing for future real-time building HVAC controls

APPLIED ENERGY 2023年第1期334卷

作者： Deng, Zhipeng Wang, Xuezheng Dong, Bing Syracuse Univ Dept Mech & Aerosp Engn Syracuse NY 13244 USA

Buildings contribute to more than 70% of overall U.S. electricity usage and greenhouse gas (GHG) emissions. HVAC systems in buildings often consume more than 40% of the total building energy usage. To reduce such high energy use, numerous control strategies including optimal and predictive controls have been developed and demonstrated. To achieve a near real-time solution, most previous research has simplified the non-linearity of building thermodynamics and provided an approximate optimal solution. The future HVAC control optimizes more connected devices in buildings, which requires a rapid and accurate response, not only to the building itself but also to the grid signals. It also poses the challenge of solving non-linear problems with discrete variables. With the recent development of quantum computers, this has become feasible. In this paper, we developed a new optimization solution based on quantum annealing for model predictive control (MPC) of a rooftop unit (RTU). Compared to traditional optimization methods, we obtained similar solutions with less than 2% differences and improved computational speed from hours to seconds. We also demonstrated an 80% reduction in total electricity consumption and a 21% reduction in electricity bills by considering day-ahead price time-of-use demand response signals. Quantum computing has proven capable of solving large-scale non-linear discrete optimization problems for building energy systems.

关键词： Discrete optimization mixed-integer programming Quadratic unconstrained binary optimization Quantum annealing Energy-efficient building

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Systematic generation of alternative production schedules

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AICHE JOURNAL 2020年第5期66卷 e16926-e16926页

作者： Lee, Hojae Gupta, Dhruv Maravelias, Christos T. Univ Wisconsin Madison Dept Chem & Biol Engn 1415 Engn Dr Madison WI 53706 USA

We propose a systematic approach for generating alternative production schedules to address two challenges in implementing optimization-based scheduling techniques in industrial settings: (a) the limited scope of the scheduling models due to modeling simplifications, and (b) the consideration of shop-floor nervousness. We first introduce metrics to quantify specific characteristics of a schedule (e.g., number of batches and degree of nervousness). Next, we favor, at different degrees, such characteristics in each alternative schedule, by penalizing the metrics in the objective function. Through illustrative instances, we show that multiple alternative schedules, including schedules with desired properties can readily be generated.

关键词： mixed-integer programming nervousness online scheduling

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An optimization-based approach for the healthcare districting under uncertainty

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COMPUTERS & OPERATIONS RESEARCH 2021年 135卷 105425-105425页

作者： Darmian, Sobhan Mostafayi Fattahi, Mohammad Keyvanshokooh, Esmaeil Univ Kurdistan Dept Ind Engn Sanandaj Iran Northumbria Univ Newcastle Business Sch Newcastle Upon Tyne Tyne & Wear England Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA

In this paper, we address a districting problem motivated by a real-world case study to partition residential areas of a region for a healthcare system operation under interval demand uncertainty of health services. A mixedinteger programming model is presented based on the graph theory that enforces contiguity constraints on districts in addition to other corresponding practical criteria. Furthermore, robust optimization approaches are extended to address the existing uncertainty. To deal with the problem's computational intractability, an improved genetic algorithm is developed in accordance with the graph-based nature of the problem obtaining near-optimal solutions on large-sized instances. Extensive computational results are presented on a real-world case study and several randomly generated instances to evaluate the applicability of the models, performance of the presented robustness measure, and effectiveness of the solution approach. Furthermore, a hierarchical districting approach that enables decision makers to obtain districting decisions in various levels of health services is examined. Sensitivity analyses on main parameters are performed to derive some managerial insights that can help practitioners in providing suitable and homogeneous health services in a geographical area.

关键词： Healthcare services Districting problem Robust optimization mixed-integer programming Graph theory Graph-based genetic algorithm

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Synchronized timetables for bus rapid transit networks in small and large cities

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SCIENTIA IRANICA 2021年第1期28卷 477-491页

作者： Ataeian, Sh Solimanpur, M. Amiripour, S. M. M. Shankar, R. Urmia Univ Dept Ind Engn Orumiyeh Iran Toos Inst Higher Educ Mashhad Razavi Khorasan Iran Indian Inst Technol Delhi Dept Management Studies New Delhi India

The quality of public transportation service has significant effects on the quality of urban life. In the course of frequency setting and timetabling as an important step in the public transportation planning process, synchronization gains significance and directly influences the utility and attractiveness of the system;therefore, a great deal of attention should be drawn to it in the whole planning process, especially in setting frequency and timetable. To this end, the present study proposes a mixed-integer nonlinear programming model to set timetables on a bus transit network with maximum synchronization and minimum number of fleet size. The proposed model is applicable to both small- and large-scale transit networks and is used for setting timetables on two samples of different sizes. A simple problem in this study was solved by General Algebraic Modeling System (GAMS) Software where the obtained timetable seemed quite reasonable. Moreover, the proposed model was employed to set timetables through the genetic algorithm on Tehran Bus Rapid Transit (BRT) networks as a real-life instance;then, the NSGA-II was used to obtain the Pareto optimal solutions of the problem for five different scenarios. Finally, the results showed that the proposed model was efficient in setting timetables on transit networks of different sizes. (C) 2021 Sharif University of Technology. All rights reserved.

关键词： Public transportation Bus line timetable setting Mathematical modeling mixed-integer programming Genetic algorithm

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Exact and heuristic approaches for the automated design of medical trainees rotation schedules

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2020年 97卷 102107-102107页

作者： Castano, Fabian Velasco, Nubia Pontificia Univ Javeriana Dept Civil & Ind Engn Calle 18 118-250 Cali Colombia Univ Los Andes Sch Management Calle 21 1-20 Bogota Colombia

This article addresses the problem of designing rotation schedules for the training of medical students in a healthcare institution in Colombia. Rotations are carried out along the course of a six months time period during which students rotate through different services both during one or multiple fortnightly periods. The hospital receives trainees from different universities that present heterogeneous requirements, and must accomplish different rotations constraints even in those cases when they come from the same university. Two different approaches are proposed to tackle the problem. First, a mathematical programming model is considered. Secondly, a metaheuristic approach based on Variable Neighborhood Search is adapted to solve the problem in an efficient manner. In both cases the objective function is proposed to be either a linear or a quadratic function that seeks a stable allocation of personnel to the services all along the considered time horizon. The proposed techniques are implemented as a part of a basic spreadsheet that helps personnel in charge generate, validate and fix the proposed plans as needed. The effectiveness of the methodology is tested through ex-post analysis, comparing it against schedules generated by the personnel in charge at the hospital, and over simulated data. The results indicate that the applied metaheuristic is competitive against specialized optimization software and facilitates the work of optimization for the health professionals in charge, reducing the planning tasks from several days to minutes. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Medical rotations Healthcare services Scheduling Medical trainees mixed-integer programming Variable neighborhood search

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Joint Design of Beamforming and Antenna Selection in Short Blocklength Regime for URLLC in Cognitive Radio Networks

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IEEE ACCESS 2021年 9卷 144676-144686页

作者： Ngo Tan Vu Khanh Tien-Tung Nguyen Univ Econ Ho Chi Minh City Sch Business Informat Technol Dept Ecommerce Technol Ho Chi Minh City 70000 Vietnam Ind Univ Ho Chi Minh City Telecommun Div Ho Chi Minh City 700000 Vietnam

This paper considers the short blocklength regime for cognitive radio networks (CRNs) to deliver ultra-reliable and low-latency communications (URLLCs) promised for beyond 5G networks. The secondary system consists of a secondary transmitter (ST) and multiple secondary users, which are allowed to access the same spectrum of licensed users (i.e., the primary system). Adopting linear beamforming at ST, we formulate the optimization problem of the energy-efficient maximization for the secondary system under the power constraint at ST and interference power constraints at primary receivers. In the short blocklength regime, the rate function is more complex and computationally intractable than the traditional Shannon rate function, which makes the formulated problem more difficult to solve. By leveraging techniques from the Dinkelbach method and the inner approximation method, we first devise newly approximated functions to convexify nonconvex constraints, and the iterative algorithm is then developed to obtain at least a locally optimal solution. To further enhance the energy efficiency of the secondary system, we consider a joint optimization of beamforming and antenna selection at ST, where binary variables are introduced to establish the operation modes of transmit antennas. To solve the mixed-integer nonconvex problem, we incorporate the penalty function into the objective function to dealing with the uncertainty of binary variables. Numerical results are provided to demonstrate the fast convergence and merits of the proposed algorithms, as well as to confirm the role of antenna selection in improving energy efficiency.

关键词： Ultra reliable low latency communication Transmitting antennas Resource management Array signal processing Reliability Optimization Interference Antenna selection beamforming broadcast channel cognitive radio Dinkelbach method energy efficiency inner approximation mixed-integer programming

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Sustainable supply chain network design: A case of the glass manufacturer in Asia

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2022年 248卷

作者： Naeeni, Hannan Sadjady Sabbaghi, Navid Longwood Univ Coll Business & Econ 201 High St Farmville VA 23909 USA St Marys Coll Calif Sch Econ Business Adm 1928 St Marys Rd Moraga CA 94575 USA

Traditionally, profit maximization was the major objective for many businesses. However, due to growing stakeholders' pressure and awareness about the social and environmental impacts of supply chain activities, many companies are now focused on optimizing their profits, while reducing negative impacts of their activities on planet and society. While sustainable development requires concurrent and balanced consideration of social, environmental and economic dimensions, unbalanced approaches have been adopted both in real world practices, and in academic literature. We contribute to the stream of research in the literature that tries to address this gap. We propose a multi-objective mixed-integer programming (MOMIP) model for sustainable supply chain network design (SSCND), encompassing economic, environmental, and social objectives. Both strategic and tactical network design decision variables are considered, including location, size, and technology type of facilities, along with determining the flow of materials and transportation modes. The Normalized Normal Constraint Method is applied to generate evenly distributed Pareto frontiers. The case of a glass manufacturing company in Asia is used to demonstrate applicability of the model and solution procedure to real-world problems. Non-dominated solutions are analyzed, and a more sustainable and balanced network design alternative is proposed, which outperforms the current network configuration in terms of all three dimensions of sustainability. Managerial implications and future research directions are discussed.

关键词： Supply chain network design Sustainability Multi-objective optimization mixed-integer programming Normalized normal constraint method

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An assessment of European electricity arbitrage using storage systems

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ENERGY 2022年 242卷 122916-122916页

作者： Nunez, Fernando Canca, David Arcos-Vargas, Angel Univ Seville Sch Engn Dept Ind Engn & Management Sci Seville Spain

Electricity arbitrage involves the storage of energy at times when prices are low, and offering it on the markets when prices are high. The development of renewable and energy storage technologies may provide a promising business opportunity for electricity arbitrage. In this regard, this study analyses the current viability of the electricity arbitrage business (via Li-Ion batteries) using a sample of European countries in the year 2019;countries where electricity prices (day-ahead market) and financial conditions show a certain degree of heterogeneity. We basically follow a sequence of three analyses in our study. Firstly, a Linear mixed-Integrated programming model has been developed to optimize the arbitrage strategy for each country in the sample. Secondly, using the cash-flows from the optimization model, we calculate two financial indicators (Net Present Value (NPV) and Internal Rate of Return) in order to select the optimal inverter size for each country. Tax and discount rates specific to each country have been used with the calculation of this second rate following the methodology proposed by most of the national agencies. Thirdly, a mixed linear regression model is proposed in order to investigate the importance of observed and unobserved heterogeneity (at country level) in explaining the business profitability. The findings show that, in the near future, the most attractive European countries for the electricity arbitrage business should be the United Kingdom and Ireland, with current NPV close to-400,000 V, while Spain and Portugal might show the worst performances, their current NPV are close to-800,000 V. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Arbitrage business with storage European wholesale electricity market International comparison Discount rate calculation mixed-integer programming mixed regression models

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A Computational Method for Estimating Travel Frequencies in Site Layout Planning

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JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT 2016年第5期142卷 04015102-04015102页

作者： Hammad, Ahmed W. A. Akbarnezhad, Ali Rey, David Waller, S. Travis Univ New S Wales Sch Civil & Environm Engn Sydney NSW 2052 Australia Univ New S Wales Sch Civil & Environm Engn rCITI Sydney NSW 2052 Australia

Optimizing the layout of facilities on a construction site to minimize the material handling costs has been widely investigated in the literature. An integral part of the objective function utilized in the previously proposed optimization models is the frequency parameter, which generally provides a rough estimate of the frequency of travel between each pair of facilities at a specific stage of the project. The majority of travel frequencies deduced in prior studies have been estimated merely based on past experience and may not be an actual representation of movements within the project studied. There is currently a lack of a systematic approach for estimating travel frequencies, required in site layout planning, based on the information available at early stages of the project. Obtaining a reasonable estimate of the travel frequency matrix requires a realistic evaluation of the material transportation quantities at each construction stage. This necessitates the utilization of information on the progress of different activities and their corresponding material needs during the various stages. This paper presents a framework for obtaining travel frequencies at different construction project phases by taking advantage of the information made available by building information models and project schedules. The estimated frequencies are later embedded as parameters in an optimization model to improve site layout planning. The results of a case study are presented to highlight the capabilities of the proposed framework. (C) 2015 American Society of Civil Engineers.

关键词： Building information modeling (BIM) Construction site layout planning Facility layout optimization mixed-integer programming Travel frequency Project planning and design

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Spatial optimization for reducing wind exposure of forest stands at the property level

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FOREST ECOLOGY AND MANAGEMENT 2021年 502卷 119649-119649页

作者： Fustel, Teresa Lopez-Andujar Eggers, Jeannette Lamas, Tomas Ohman, Karin Swedish Univ Agr Sci Dept Forest Resource Management SE-90183 Umea Sweden

Storms constitute one of the major natural disturbances in Sweden and its associated damages appear to be in an upward trend during the last 35 years in Europe. In addition, storm damages are expected to increase in the future due to the shortening of the soil frost period during the winter caused by climate change. Here we present a new optimization model to be used in forest planning for decreasing the wind exposure for storms over time through the minimization of vulnerable edges between neighbouring stands in a forest property. Three different cases were investigated where height differences of 5, 10 and 15 m between neighbouring stands were used to identify vulnerable edges in the property. The model, which accounts for the higher sensitivity of spruce compared to other tree species, was formulated as a mixed integer programming problem and solved using a branch and bound algorithm in a case study for a forest property in southern Sweden. In the case study, we investigated the trade-off between minimizing the length of vulnerable stand edges and the net present value from wood production. Our results show that it is possible to decrease vulnerable edge length with relatively moderate declines in the maximum achievable net present value, resulting in a clustering of dominant heights of neighbouring stands. Larger decreases in vulnerable edge length led to larger decreases in net present value, and an increased area proportion of forest older than 80 years. This model can easily be adapted to other planning problems in which edge effects are important.

关键词： Forest planning mixed-integer programming Storm damage Decision support system

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