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Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

《能源前沿（英文）》 doi: 10.1007/s11708-023-0912-6

摘要： With the promotion of “dual carbon” strategy, data center (DC) access to high-penetration renewable energy sources (RESs) has become a trend in the industry. However, the uncertainty of RES poses challenges to the safe and stable operation of DCs and power grids. In this paper, a multi-timescale optimal scheduling model is established for interconnected data centers (IDCs) based on model predictive control (MPC), including day-ahead optimization, intraday rolling optimization, and intraday real-time correction. The day-ahead optimization stage aims at the lowest operating cost, the rolling optimization stage aims at the lowest intraday economic cost, and the real-time correction aims at the lowest power fluctuation, eliminating the impact of prediction errors through coordinated multi-timescale optimization. The simulation results show that the economic loss is reduced by 19.6%, and the power fluctuation is decreased by 15.23%.

关键词： model predictive control     interconnected data center     multi-timescale     optimized scheduling     distributed power supply     landscape uncertainty    

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concentration of gluconic acid from an integrated fermentation and membrane process using response surface optimized

Parimal Pal, Ramesh Kumar, Subhamay Banerjee

《化学科学与工程前沿（英文）》 2019年 第13卷 第1期   页码 152-163 doi: 10.1007/s11705-018-1721-z

摘要： A response surface method was used to optimize the purification and concentration of gluconic acid from fermentation broth using an integrated membrane system. was used for the bioconversion of the glucose in sugarcane juice to gluconic acid (concentration 45 g?L ) with a yield of 0.9 g?g . The optimum operating conditions, such as trans-membrane pressure (TMP), pH, cross-flow rate (CFR) and initial gluconic acid concentration, were determined using response surface methodology. Five different types of polyamide nanofiltration membranes were screened and the best performing one was then used for downstream purification of gluconic acid in a flat sheet cross-flow membrane module. Under the optimum conditions (TMP= 12 bar and CFR= 400 L?h ), this membrane retained more than 85% of the unconverted glucose from the fermentation broth and had a gluconic acid permeation rate of 88% with a flux of 161 L?m ?h . Using response surface methods to optimize this green nanofiltration process is an effective way of controlling the production of gluconic acid so that an efficient separation with high flux is obtained.

关键词： gluconic acid     optimized nanofiltration     green processing     process intensification    

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Erratum to: Optimized determination of airborne tetracycline resistance genes in laboratory atmosphere

Lu Song, Can Wang, Yizhu Wang

《环境科学与工程前沿（英文）》 2020年 第14卷 第6期 doi: 10.1007/s11783-020-1289-y

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Dynamic simulation based optimized design method of concrete production system for RCC dam

ZHAO Chunju, ZHOU Yihong

《结构与土木工程前沿（英文）》 2007年 第1卷 第4期   页码 405-410 doi: 10.1007/s11709-007-0055-6

摘要： The construction system of roller compacted concrete (RCC) dam is running according to a series of connected procedures which are highly impacted and interacted consisting with the resource level. Therefore, a dynamic simulation mode

关键词： interacted     dynamic simulation     construction     resource     RCC    

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Development and challenges of planning and scheduling for petroleum and petrochemical production

Fupei LI, Minglei YANG, Wenli DU, Xin DAI

《工程管理前沿（英文）》 2020年 第7卷 第3期   页码 373-383 doi: 10.1007/s42524-020-0123-3

摘要： Production planning and scheduling are becoming the core of production management, which support the decision of a petrochemical company. The optimization of production planning and scheduling is attempted by every refinery because it gains additional profit and stabilizes the daily production. The optimization problem considered in industry and academic research is of different levels of realism and complexity, thus increasing the gap. Operation research with mathematical programming is a conventional approach used to address the planning and scheduling problem. Additionally, modeling the processes, objectives, and constraints and developing the optimization algorithms are significant for industry and research. This paper introduces the perspective of production planning and scheduling from the development viewpoint.

关键词： planning and scheduling     optimization     modeling    

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Lessons learned from developing and implementing refinery production scheduling technologies

Marcel JOLY, Mario Y. MIYAKE

《工程管理前沿（英文）》 2017年 第4卷 第3期   页码 325-337 doi: 10.15302/J-FEM-2017033

摘要： An increasing number of novel and highly specialized computer-aided decision-making technologies for short-term production scheduling in oil refineries has emerged and evolved over the past two decades, thereby encouraging refiners to permanently rethink the way the refining business is operated and managed. In this report, we discuss the key lessons learned from one of the pioneering, yet daring, enterprise-wide programs entirely implemented in an energy company devoted to developing and implementing an advanced refinery production scheduling (RPS) technology, i.e., the RPS system of Petrobras. Apart from mathematical and information technology issues, the long-term sustainability of a successful RPS project is, we argue, the outcome of a virtuous cycle grounded on permanent actions devoted to improving technical education inside the organization, reinspecting organizational cultures and operational paradigms, and developing working processes.

关键词： automation     decision making     oil refinery     optimization     production scheduling    

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A review of intelligent optimization for group scheduling problems in cellular manufacturing

《工程管理前沿（英文）》   页码 406-426 doi: 10.1007/s42524-022-0242-0

摘要： Given that group technology can reduce the changeover time of equipment, broaden the productivity, and enhance the flexibility of manufacturing, especially cellular manufacturing, group scheduling problems (GSPs) have elicited considerable attention in the academic and industry practical literature. There are two issues to be solved in GSPs: One is how to allocate groups into the production cells in view of major setup times between groups and the other is how to schedule jobs in each group. Although a number of studies on GSPs have been published, few integrated reviews have been conducted so far on considered problems with different constraints and their optimization methods. To this end, this study hopes to shorten the gap by reviewing the development of research and analyzing these problems. All literature is classified according to the number of objective functions, number of machines, and optimization algorithms. The classical mathematical models of single-machine, permutation, and distributed flowshop GSPs based on adjacent and position-based modeling methods, respectively, are also formulated. Last but not least, outlooks are given for outspread problems and problem algorithms for future research in the fields of group scheduling.

关键词： cellular manufacturing     group scheduling     flowshop     literature review    

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the terrain adaptability of a multirobot cooperative transportation system via novel connectors and optimized

《机械工程前沿（英文）》 2023年 第18卷 第3期 doi: 10.1007/s11465-023-0754-2

摘要： Given limited terrain adaptability, most existing multirobot cooperative transportation systems (MRCTSs) mainly work on flat pavements, restricting their outdoor applications. The connectors’ finite deformation capability and the control strategies’ limitations are primarily responsible for this phenomenon. This study proposes a novel MRCTS based on tracked mobile robots (TMRs) to improve terrain adaptability and expand the application scenarios of MRCTSs. In structure design, we develop a novel 6-degree-of-freedom passive adaptive connector to link multiple TMRs and the transported object (the communal payload). In addition, the connector is set with sensors to measure the position and orientation of the robot with respect to the object for feedback control. In the control strategy, we present a virtual leader–physical follower collaborative paradigm. The leader robot is imaginary to describe the movement of the entire system and manage the follower robots. All the TMRs in the system act as follower robots to transport the object cooperatively. Having divided the whole control structure into the leader robot level and the follower robot level, we convert the motion control of the two kinds of robots to trajectory tracking control problems and propose a novel double closed-loop kinematics control framework. Furthermore, a control law satisfying saturation constraints is derived to ensure transportation stability. An adaptive control algorithm processes the wheelbase uncertainty of the TMR. Finally, we develop a prototype of the TMR-based MRCTS for experiments. In the trajectory tracking experiment, the developed MRCTS with the proposed control scheme can converge to the reference trajectory in the presence of initial tracking errors in a finite time. In the outdoor experiment, the proposed MRCTS consisting of four TMRs can successfully transport a payload weighing 60 kg on an uneven road with the single TMR’s maximum load limited to 15 kg. The experimental results demonstrate the effectiveness of the structural design and control strategies of the TMR-based MRCTS.

关键词： multirobot system     cooperative transportation     terrain adaptability     trajectory tracking     collaborative paradigm     uneven road    

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A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

《环境科学与工程前沿（英文）》 2023年 第17卷 第7期 doi: 10.1007/s11783-023-1688-y

摘要：

● A novel VMD-IGOA-LSTM model has proposed for the prediction of water quality.

关键词： Water quality prediction     Grasshopper optimization algorithm     Variational mode decomposition     Long short-term memory neural network    

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A carbon efficiency upgrading method for mechanical machining based on scheduling optimization strategy

Shuo ZHU, Hua ZHANG, Zhigang JIANG, Bernard HON

《机械工程前沿（英文）》 2020年 第15卷 第2期   页码 338-350 doi: 10.1007/s11465-019-0572-8

摘要： Low-carbon manufacturing (LCM) is increasingly being regarded as a new sustainable manufacturing model of carbon emission reduction in the manufacturing industry. In this paper, a two-stage low-carbon scheduling optimization method of job shop is presented as part of the efforts to implement LCM, which also aims to reduce the processing cost and improve the efficiency of a mechanical machining process. In the first stage, a task assignment optimization model is proposed to optimize carbon emissions without jeopardizing the processing efficiency and the profit of a machining process. Non-dominated sorting genetic algorithm II and technique for order preference by similarity to an ideal solution are then adopted to assign the most suitable batch task of different parts to each machine. In the second stage, a processing route optimization model is established to plan the processing sequence of different parts for each machine. Finally, niche genetic algorithm is utilized to minimize the makespan. A case study on the fabrication of four typical parts of a machine tool is demonstrated to validate the proposed method.

关键词： Low-carbon manufacturing     carbon efficiency     multi-objective optimization     two-stage scheduling     job shop    

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Water quality soft-sensor prediction in anaerobic process using deep neural network optimized by Tree-structured

《环境科学与工程前沿（英文）》 2023年 第17卷 第6期 doi: 10.1007/s11783-023-1667-3

摘要：

● Hybrid deep-learning model is proposed for water quality prediction.

关键词： Water quality prediction     Soft-sensor     Anaerobic process     Tree-structured Parzen Estimator    

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Refinery production scheduling toward Industry 4.0

Marcel JOLY, Darci ODLOAK, Mario Y. MIYAKE, Brenno C. MENEZES, Jeffrey D. KELLY

《工程管理前沿（英文）》 2018年 第5卷 第2期   页码 202-213 doi: 10.15302/J-FEM-2017024

摘要： Understanding the holistic relationship between refinery production scheduling (RPS) and the cyber-physical production environment with smart scheduling is a new question posed in the study of process systems engineering. Here, we discuss state-of-the-art RSPs in the crude-oil refining field and present examples that illustrate how smart scheduling can impact operations in the high-performing chemical process industry. We conclude that, more than any traditional off-the-shelf RPS solution available today, flexible and integrative specialized modeling platforms will be increasingly necessary to perform decentralized and collaborative optimizations, since they are the technological alternatives closer to the advanced manufacturing philosophy.

关键词： cyber-physical systems     optimization     petrochemical industry     scheduling     smart manufacturing    

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Optimal design of double-layer barrel vaults using genetic and pattern search algorithms and optimized

《结构与土木工程前沿（英文）》 2023年 第17卷 第3期   页码 378-395 doi: 10.1007/s11709-022-0899-9

摘要： This paper presents a combined method based on optimized neural networks and optimization algorithms to solve structural optimization problems. The main idea is to utilize an optimized artificial neural network (OANN) as a surrogate model to reduce the number of computations for structural analysis. First, the OANN is trained appropriately. Subsequently, the main optimization problem is solved using the OANN and a population-based algorithm. The algorithms considered in this step are the arithmetic optimization algorithm (AOA) and genetic algorithm (GA). Finally, the abovementioned problem is solved using the optimal point obtained from the previous step and the pattern search (PS) algorithm. To evaluate the performance of the proposed method, two numerical examples are considered. In the first example, the performance of two algorithms, OANN + AOA + PS and OANN + GA + PS, is investigated. Using the GA reduces the elapsed time by approximately 50% compared with using the AOA. Results show that both the OANN + GA + PS and OANN + AOA + PS algorithms perform well in solving structural optimization problems and achieve the same optimal design. However, the OANN + GA + PS algorithm requires significantly fewer function evaluations to achieve the same accuracy as the OANN + AOA + PS algorithm.

关键词： optimization     surrogate models     artificial neural network     SAP2000     genetic algorithm    

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Energy-aware scheduling with reconstruction and frequency equalization on heterogeneous systems

Yong-xing LIU,Ken-li LI,Zhuo TANG,Ke-qin LI

《信息与电子工程前沿（英文）》 2015年 第16卷 第7期   页码 519-531 doi: 10.1631/FITEE.1400399

摘要： With the increasing energy consumption of computing systems and the growing advocacy for green computing, energy efficiency has become one of the critical challenges in high-performance heterogeneous computing systems. Energy consumption can be reduced by not only hardware design but also software design. In this paper, we propose an energy-aware scheduling algorithm with equalized frequency, called EASEF, for parallel applications on heterogeneous computing systems. The EASEF approach aims to minimize the finish time and overall energy consumption. First, EASEF extracts the set of paths from an application. Then, it reconstructs the application based on the extracted set of paths to achieve a reasonable schedule. Finally, it adopts a progressive way to equalize the frequency of tasks to reduce the total energy consumption of systems. Randomly generated applications and two real-world applications are examined in our experiments. Experimental results show that the EASEF algorithm outperforms two existing algorithms in terms of makespan and energy consumption.

关键词： Directed acyclic graph     Dynamic voltage scaling     Energy aware     Heterogeneous systems     Task scheduling    

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Decision Support System for emergency scheduling of raw water supply systems with multiple sources

Qi WANG, Shuming LIU, Wenjun LIU, Zoran KAPELAN, Dragan SAVIC

《环境科学与工程前沿（英文）》 2013年 第7卷 第5期   页码 777-786 doi: 10.1007/s11783-013-0537-9

摘要： A hydraulic model-based emergency scheduling Decision Support System (DSS) is designed to eliminate the impact of sudden contamination incidents occurring upstream in raw water supply systems with multiple sources. The DSS consists of four functional modules, including water quality prediction, system safety assessment, emergency strategy inference and scheduling optimization. The work flow of the DSS is as follows. First, the water quality variations on specific cross-sections are calculated given the pollution information. Next, a comprehensive evaluation on the safety of the current system is conducted using the outputs in the first module. This will assist in the assessment of whether the system is in danger of failure, taking both the impact of pollution and system capacity into account. If there is a severe impact of contamination on the reliability of the system, a fuzzy logic based inference module is employed to generate reasonable strategies including technical measures. Otherwise, a Genetic Algorithm (GA)-based optimization model will be used to find the least-cost scheduling plan. The proposed DSS has been applied to a coastal city in South China during a saline tide period as validation. Through scenario analysis, it is demonstrated that this DSS tool is instrumental in emergency scheduling for the water company to quickly and effectively respond to sudden contamination incidents.

关键词： decision support system     raw water supply system     contamination incident     emergency scheduling     hydraulic model     safety assessment    

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标题 作者 时间 类型 操作

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

期刊论文

concentration of gluconic acid from an integrated fermentation and membrane process using response surface optimized

Parimal Pal, Ramesh Kumar, Subhamay Banerjee

期刊论文

Erratum to: Optimized determination of airborne tetracycline resistance genes in laboratory atmosphere

Lu Song, Can Wang, Yizhu Wang

期刊论文

Dynamic simulation based optimized design method of concrete production system for RCC dam

ZHAO Chunju, ZHOU Yihong

期刊论文

Development and challenges of planning and scheduling for petroleum and petrochemical production

Fupei LI, Minglei YANG, Wenli DU, Xin DAI

期刊论文

Lessons learned from developing and implementing refinery production scheduling technologies

Marcel JOLY, Mario Y. MIYAKE

期刊论文

A review of intelligent optimization for group scheduling problems in cellular manufacturing

期刊论文

the terrain adaptability of a multirobot cooperative transportation system via novel connectors and optimized

期刊论文

A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

期刊论文

A carbon efficiency upgrading method for mechanical machining based on scheduling optimization strategy

Shuo ZHU, Hua ZHANG, Zhigang JIANG, Bernard HON

期刊论文

Water quality soft-sensor prediction in anaerobic process using deep neural network optimized by Tree-structured

期刊论文

Refinery production scheduling toward Industry 4.0

Marcel JOLY, Darci ODLOAK, Mario Y. MIYAKE, Brenno C. MENEZES, Jeffrey D. KELLY

期刊论文

Optimal design of double-layer barrel vaults using genetic and pattern search algorithms and optimized

期刊论文

Energy-aware scheduling with reconstruction and frequency equalization on heterogeneous systems

Yong-xing LIU,Ken-li LI,Zhuo TANG,Ke-qin LI

期刊论文

Decision Support System for emergency scheduling of raw water supply systems with multiple sources

Qi WANG, Shuming LIU, Wenjun LIU, Zoran KAPELAN, Dragan SAVIC

期刊论文