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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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MPC-based interval number optimization for electric water heater scheduling in uncertain environments

Jidong WANG, Chenghao LI, Peng LI, Yanbo CHE, Yue ZHOU, Yinqi LI

《能源前沿（英文）》 2021年第15卷第1期页码 186-200 doi: 10.1007/s11708-019-0644-9

摘要： In this paper, interval number optimization and model predictive control are proposed to handle the uncertain-but-bounded parameters in electric water heater load scheduling. First of all, interval numbers are used to describe uncertain parameters including hot water demand, ambient temperature, and real-time price of electricity. Moreover, the traditional thermal dynamic model of electric water heater is transformed into an interval number model, based on which, the day-ahead load scheduling problem with uncertain parameters is formulated, and solved by interval number optimization. Different tolerance degrees for constraint violation and temperature preferences are also discussed for giving consumers more choices. Furthermore, the model predictive control which incorporates both forecasts and newly updated information is utilized to make and execute electric water heater load schedules on a rolling basis throughout the day. Simulation results demonstrate that interval number optimization either in day-ahead optimization or model predictive control format is robust to the uncertain hot water demand, ambient temperature, and real-time price of electricity, enabling customers to flexibly adjust electric water heater control strategy.

关键词： electric water heater load scheduling interval number optimization model predictive control uncertainty

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Long-term simulation of growth stage-based irrigation scheduling in maize under various water constraints

Quanxiao FANG, Liwang MA, Lajpat Rai AHUJA, Thomas James TROUT, Robert Wayne MALONE, Huihui ZHANG, Dongwei GUI, Qiang YU

《农业科学与工程前沿（英文）》 2017年第4卷第2期页码 172-184 doi: 10.15302/J-FASE-2017139

摘要： Due to varying crop responses to water stress at different growth stages, scheduling irrigation is a challenge for farmers, especially when water availability varies on a monthly, seasonal and yearly basis. The objective of this study was to optimize irrigation between the vegetative (V) and reproductive (R) phases of maize under different available water levels in Colorado. Long-term (1992–2013) scenarios simulated with the calibrated Root Zone Water Quality Model were designed to meet 40%–100% of crop evapotranspiration (ET) requirements at V and R phases, subject to seasonal water availabilities (300, 400, 500 mm, and no water limit), with and without monthly limits (total of 112 scenarios). The most suitable irrigation between V and R phases of maize was identified as 60/100, 80/100, and 100/100 of crop ET requirement for the 300, 400, 500 mm water available, respectively, based on the simulations from 1992 to 2013. When a monthly water limit was imposed, the corresponding suitable irrigation targets between V and R stages were 60/100, 100/100, and 100/100 of crop ET requirement for the above three seasonal water availabilities, respectively. Irrigation targets for producing higher crop yield with reduced risk of poor yield were discussed for projected five-year water availabilities.

关键词： RZWQM ET-based irrigation schedule maize water constrains

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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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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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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 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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Enterprise-wide optimization of integrated planning and scheduling for refinery-petrochemical complex

《化学科学与工程前沿（英文）》 doi: 10.1007/s11705-022-2283-7

摘要： This paper focuses on the integrated problem of long-term planning and short-term scheduling in a large-scale refinery-petrochemical complex, and considers the overall manufacturing process from the upstream refinery to the downstream petrochemical site. Different time scales are incorporated from the planning and scheduling subproblems. At the end of each discrete time period, additional constraints are imposed to ensure material balance between different time scales. Discrete time representation is applied to the planning subproblem, while continuous time is applied to the scheduling of ethylene cracking and polymerization processes in the petrochemical site. An enterprise-wide mathematical model is formulated through mixed integer nonlinear programming. To solve the problem efficiently, a heuristic algorithm combined with a convolutional neural network (CNN), is proposed. Binary variables are used as the CNN input, leading to the integration of a data-driven approach and classical optimization by which a heuristic algorithm is established. The results do not only illustrate the detailed operations in a refinery and petrochemical complex under planning and scheduling, but also confirm the high efficiency of the proposed algorithm for solving large-scale problems.

关键词： planning scheduling refinery-petrochemical convolutional neural network heuristic algorithm

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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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Novel slack-based robust scheduling rule for a semiconductor manufacturing system with uncertain processing

Juan LIU, Fei QIAO, Yumin MA, Weichang KONG

《工程管理前沿（英文）》 2018年第5卷第4期页码 507-514 doi: 10.15302/J-FEM-2018045

摘要：

The NP-hard scheduling problems of semiconductor manufacturing systems (SMSs) are further complicated by stochastic uncertainties. Reactive scheduling is a common dynamic scheduling approach where the scheduling scheme is refreshed in response to real-time uncertainties. The scheduling scheme is overly sensitive to the emergence of uncertainties because the optimization of performance (such as minimum make-span) and the system robustness cannot be achieved simultaneously by conventional reactive scheduling methods. To improve the robustness of the scheduling scheme, we propose a novel slack-based robust scheduling rule (SR) based on the analysis of robustness measurement for SMS with uncertain processing time. The decision in the SR is made in real time given the robustness. The proposed SR is verified under different scenarios, and the results are compared with the existing heuristic rules. Simulation results show that the proposed SR can effectively improve the robustness of the scheduling scheme with a slight performance loss.

关键词： semiconductor manufacturing system uncertain processing time dynamic scheduling slack-based robust scheduling rule

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Total phosphorus accident pollution and emergency response study based on geographic information system in Three Gorges Reservoir area

Aifeng Zhai, Xiaowen Ding, Lin Liu, Quan Zhu, Guohe Huang

《环境科学与工程前沿（英文）》 2020年第14卷第3期 doi: 10.1007/s11783-020-1223-3

摘要： A new algorithm of two-dimensional water quantity and the quality model was built. The migration and diffusion of TP was simulated. The emergency measures for sudden water pollution accidents was proposed. In recent years, sudden water pollution accidents in China’s rivers have become more frequent, resulting in considerable effects on environmental safety. Therefore, it is necessary to simulate and predict pollution accidents. Simulation and prediction provide strong support for emergency disposal and disaster reduction. This paper describes a new two-dimensional water quantity and the quality model that incorporates a digital elevation model into the geographic information system. The model is used to simulate sudden water pollution accidents in the main stream of the Yangtze River and Jialing River in the Chongqing section of the Three Gorges Reservoir area. The sectional velocity distribution and concentration change of total phosphorus are then analyzed under four hydrological situations. The results show that the proposed model accurately simulates and predicts the concentration change and migration process of total phosphorus under sudden water pollution accidents. The speed of migration and diffusion of pollutants is found to be greatest in the flood season, followed by the water storage period, drawdown season, and dry season, in that order. The selection of an appropriate water scheduling scheme can reduce the peak concentration of river pollutants. This study enables the impact of pollutants on the ecological environment of river water to be alleviated, and provides a scientific basis for the emergency response to sudden water pollution accidents in the Three Gorges Reservoir area.

关键词： Sudden water pollution accident Total phosphorus Predictive model Contaminant simulation Water scheduling Measure

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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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生产调度的稳定性研究

李歧强,史开泉

《中国工程科学》 2001年第3卷第3期页码 75-79

摘要：

生产调度中存在着大量的约束条件，它是否可行完全取决于所有约束条件是否都满足。文章研究了面向约束的调度稳定性问题。给出了硬约束、软约束和约束满意度的定义，提出了调度稳定度的概念，最后给出一个生产调度案例说明了调度稳定度在生产实际中应用的意义。

关键词：生产调度约束满意度调度稳定度

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Multi-objective optimization for the multi-mode finance-based project scheduling problem

Sameh Al-SHIHABI, Mohammad AlDURGAM

《工程管理前沿（英文）》 2020年第7卷第2期页码 223-237 doi: 10.1007/s42524-020-0097-1

摘要： The finance-based scheduling problem (FBSP) is about scheduling project activities without exceeding a credit line financing limit. The FBSP is extended to consider different execution modes that result in the multi-mode FBSP (MMFBSP). Unfortunately, researchers have abandoned the development of exact models to solve the FBSP and its extensions. Instead, researchers have heavily relied on the use of heuristics and meta-heuristics, which do not guarantee solution optimality. No exact models are available for contractors who look for optimal solutions to the multi-objective MMFBSP. CPLEX, which is an exact solver, has witnessed a significant decrease in its computation time. Moreover, its current version, CPLEX 12.9, solves multi-objective optimization problems. This study presents a mixed-integer linear programming model for the multi-objective MMFBSP. Using CPLEX 12.9, we discuss several techniques that researchers can use to optimize a multi-objective MMFBSP. We test our model by solving several problems from the literature. We also show how to solve multi-objective optimization problems by using CPLEX 12.9 and how computation time increases as problem size increases. The small increase in computation time compared with possible cost savings make exact models a must for practitioners. Moreover, the linear programming-relaxation of the model, which takes seconds, can provide an excellent lower bound.

关键词： multi-objective optimization finance-based scheduling multi-mode project scheduling mixed-integer linear programming CPLEX

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Energy-aware fuzzy job-shop scheduling for engine remanufacturing at the multi-machine level

Jiali ZHAO, Shitong PENG, Tao LI, Shengping LV, Mengyun LI, Hongchao ZHANG

《机械工程前沿（英文）》 2019年第14卷第4期页码 474-488 doi: 10.1007/s11465-019-0560-z

摘要： The rise of the engine remanufacturing industry has resulted in increased possibilities of energy conservation during the remanufacturing process, and scheduling could exert significant effects on the energy performance of manufacturing systems. However, only a few studies have specifically addressed energy-efficient scheduling for remanufacturing. Considering the uncertain processing time and routes and the operation characteristics of remanufacturing, we used the crankshaft as an illustrative case and built a fuzzy job-shop scheduling model to minimize the energy consumption during remanufacturing. An improved adaptive genetic algorithm was developed by using the hormone modulation mechanism to deal with the scheduling problem that simultaneously involves parallel machines, batch machines, and uncertain processing routes and time. The algorithm demonstrated superior performance in terms of optimal value, run time, and convergent generation in comparison with other algorithms. Computational results indicated that the optimal scheduling scheme is expected to generate 1.7 kW∙h of energy saving for the investigated problem size. In addition, the scheme could improve the energy efficiency of the crankshaft remanufacturing process by approximately 5%. This study provides a basis for production managers to improve the sustainability of remanufacturing through energy-aware scheduling.

关键词： remanufacturing scheduling adaptive genetic algorithm energy efficiency sustainable remanufacturing hormone modulation mechanism

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标题作者时间类型操作

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

MPC-based interval number optimization for electric water heater scheduling in uncertain environments

Jidong WANG, Chenghao LI, Peng LI, Yanbo CHE, Yue ZHOU, Yinqi LI

期刊论文

Long-term simulation of growth stage-based irrigation scheduling in maize under various water constraints

Quanxiao FANG, Liwang MA, Lajpat Rai AHUJA, Thomas James TROUT, Robert Wayne MALONE, Huihui ZHANG, Dongwei GUI, Qiang YU

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

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

期刊论文

Lessons learned from developing and implementing refinery production scheduling technologies

Marcel JOLY, Mario Y. MIYAKE

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

Enterprise-wide optimization of integrated planning and scheduling for refinery-petrochemical complex

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

Novel slack-based robust scheduling rule for a semiconductor manufacturing system with uncertain processing

Juan LIU, Fei QIAO, Yumin MA, Weichang KONG

期刊论文

Total phosphorus accident pollution and emergency response study based on geographic information system in Three Gorges Reservoir area

Aifeng Zhai, Xiaowen Ding, Lin Liu, Quan Zhu, Guohe Huang

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

生产调度的稳定性研究

李歧强,史开泉

期刊论文

Multi-objective optimization for the multi-mode finance-based project scheduling problem

Sameh Al-SHIHABI, Mohammad AlDURGAM

期刊论文

Energy-aware fuzzy job-shop scheduling for engine remanufacturing at the multi-machine level

Jiali ZHAO, Shitong PENG, Tao LI, Shengping LV, Mengyun LI, Hongchao ZHANG

期刊论文

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