Nowadays it is known that the thermomechanical schedules applied during hot rolling of flat products provide the steel with improved mechanical properties.In this work an optimisation tool,OptiLam (OptiLam v.1),based ...Nowadays it is known that the thermomechanical schedules applied during hot rolling of flat products provide the steel with improved mechanical properties.In this work an optimisation tool,OptiLam (OptiLam v.1),based on a predictive software and capable of generating optimised rolling schedules to obtain the desired mechanical properties in the final product is described.OptiLam includes some well-known metallurgical models which predict microstructural evolution during hot rolling and the transformation austenite/ferrite during the cooling.Furthermore,an optimisation algorithm,which is based on the gradient method,has been added,in order to design thermomechanical sequences when a specific final grain size is desired.OptiLam has been used to optimise rolling parameters,such as strain and temperature.Here,some of the results of the software validation performed by means of hot torsion tests are presented,showing also the functionality of the tool.Finally,the application of classical optimisation models,based on the gradient method,to hot rolling operations,is also discussed.展开更多
Background: The optimal dose of palliative radiotherapy (RT) in symptomatic advanced lung cancer is unclear. Patients and methods: Patients with advanced NSCLC who were indicated for thoracic palliative RT with age up...Background: The optimal dose of palliative radiotherapy (RT) in symptomatic advanced lung cancer is unclear. Patients and methods: Patients with advanced NSCLC who were indicated for thoracic palliative RT with age up to 65 y and Performance Status (PS) 0 - 2 and no significant cardiac or lung co-morbidities were randomized into two fractionation arms: arm A: 30 Gy/10 over 2 weeks and arm B: 27 Gy/6 over 3 weeks (2 fractions per week) using 2 anterior posterior (AP-PA) fields in both arms. Primary end points were symptomatic and radiological tumor response, respiratory functions assessment. Secondary end point was toxicity. Results: From December 2014 to October 2015, 40 patients were randomized, 20 patients in each arm. There was statistically insignificant higher symptomatic improvement in arm B. Four weeks after treatment, 12 out of 40 patients (30%), 6 patients in each arm, had radiological Partial Response (PR) of the primary thoracic lesion without significant difference between the two arms. There was a tendency for improvement in the post treatment mean Forced Vital Capacity (FVC) and Forced Expiratory Volume in one second (FEV1) in each arm without statistical significance. There were no reported skin reactions or esophagitis in both arms up to 4 weeks after treatment. Eleven out of the 40 patients (27.5%), 6 in arm B and 5 in arm A, had radiological signs of radiation pneumonitis without significant difference between both arms. Conclusion: The two RT fractionation schedules showed equal efficacy in terms of symptoms relief, radiological response of the primary thoracic tumor, respiratory functions and toxicity. Thus the 27 Gy/6 fractionation arm appears preferable compared to 30 Gy/10 arm to minimize the patients’ visits and load on the machines.展开更多
1. Organized and attended the Discussion on "Measures for Administration of Commercial Franchise Operations" with Ministry of Commerce in January, 2005.
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Active schedule is one of the most basic and popular concepts in production scheduling research. For identical parallel machine scheduling with jobs＇ dynamic arrivals, the tight performance bounds of active schedules...Active schedule is one of the most basic and popular concepts in production scheduling research. For identical parallel machine scheduling with jobs＇ dynamic arrivals, the tight performance bounds of active schedules under the measurement of four popular objectives are respectively given in this paper. Similar analysis method and conclusions can be generalized to static identical parallel machine and single machine scheduling problem.展开更多
The microstructures and mechanical properties of three X80 pipeline steel plates were investigated in this study.The plates were hot rolled by two stages, and cooled by three different cooling schedules to obtain diff...The microstructures and mechanical properties of three X80 pipeline steel plates were investigated in this study.The plates were hot rolled by two stages, and cooled by three different cooling schedules to obtain different microstructures and mechanical properties.Transmission electron microscope（TEM） was used to observe the microstructure.The results indicated that the amount of polygonal ferrite（PF） and quasi-polygonal ferrite（QPF） decreased with decreasing of the finish cooling temperature（FCT）, while the amount and size of M-A islands were larger.Relaxation promoted the Charpy V-notch（CVN） impact toughness at-20℃, but not the drop weight tear testing（DWTT） property at-15℃, and decreased the strength of the steel.展开更多
Drip irrigation system can achieve high uniformity. When the system is designed for uniformity coefficient equal or more than 70%, the water application in the field can be expressed as a normal distribution and furth...Drip irrigation system can achieve high uniformity. When the system is designed for uniformity coefficient equal or more than 70%, the water application in the field can be expressed as a normal distribution and further simplified to a linear distribution. This paper will describe the irrigation scheduling parameters, percent of deficit, application efficiency and coefficient of variation by simple mathematical model. Using this effective model and the irrigation application, the total yield affected by the total water application for different uniformity of irrigation application can be determined. More over, this paper uses the cost of water, price of yield, uniformity of the drip irrigation system, crop response to water application and environmental concerns of pollution and contamination to determine the optimal irrigation schedule. A case study shows that the optimal irrigation schedule can achieve the effect of water saving and production increment compared with the conventional irrigation schedule in which the whole field is fully irrigated.展开更多
To minimize the deviations of the net present values of project payment for both the owner and the client and optimize project payment schedules, a Nash equilibrium model based on game theory was set up and a genetic ...To minimize the deviations of the net present values of project payment for both the owner and the client and optimize project payment schedules, a Nash equilibrium model based on game theory was set up and a genetic algorithm was developed to work out the Nash equilibrium solution with a two-stage backward inductive approach that requires the client responds to the owner’s payment schedule with an activity schedule so as to maximize the client’s net present value of cash flows. A case study demonstrated that a payment schedule at the Nash equilibrium position enables both the owner and the client to gain their desirable interests, thus is a win-win solution for both parties. Despite the computation time of the proposed algrithm in need of improving, combining Nash equilibrium and genetic algorithm into a complete-information dynamic-game model is a promising method for project management optimization.展开更多
The increased concern over global climate change and lack of long-term sustainability of fossil fuels in the projected future has prompted further research into advanced alternative fuel vehicles to reduce vehicle emi...The increased concern over global climate change and lack of long-term sustainability of fossil fuels in the projected future has prompted further research into advanced alternative fuel vehicles to reduce vehicle emissions and fuel consumption. One of the primary advanced vehicle research areas involves electrification and hybridization of vehicles. As hybrid-electric vehicle technology has advanced, so has the need for more innovative control schemes for hybrid vehicles, including the development and optimization of hybrid powertrain transmission shift schedules. The hybrid shift schedule works in tandem with a cost function-based torque split algorithm that dynamically determines the optimal torque command for the electric motor and engine. The focus of this work is to develop and analyze the benefits and limitations of two different shift schedules for a position-3 (P3) parallel hybrid-electric vehicle. a traditional two-parameter shift schedule that operates as a function of vehicle accelerator position and vehicle speed (state of charge (SOC) independent shift schedule), and a three-parameter shift schedule that also adapts to fluctuations in the state of charge of the high voltage batteries (SOC dependent shift schedule). The shift schedules were generated using an exhaustive search coupled with a fitness function to evaluate all possible vehicle operating points. The generated shift schedules were then tested in the software-in-the-loop (SIL) environment and the vehicle-in-the-loop (VIL) environment and compared to each other, as well as to the stock 8L45 8-speed transmission shift schedule. The results show that both generated shift schedules improved upon the stock transmission shift schedule used in the hybrid powertrain comparing component efficiency, vehicle efficiency, engine fuel economy, and vehicle fuel economy.展开更多
Two problems for task schedules in a multiprocessor parallel system are discussed in Ans paper (1) given a partially ordered set of tasks represented by the venices of an acyclic directed graph with their correspondin...Two problems for task schedules in a multiprocessor parallel system are discussed in Ans paper (1) given a partially ordered set of tasks represented by the venices of an acyclic directed graph with their corresponding processing bines, derive the lower bound on the Annimum time(LBMT) needed to process the task graph for a given number of processors. (2) Determine the lower bound on minimum number of processors(LBMP) needed to complete those tasks in minimum bine. It is shown that the proposed LBMT is sharper than previously Known values and the comPUtational aspeCts of these bounds are also discussed.展开更多
A field experiment was conducted to elucidate the regulation mechanism of different irrigation schedules on population photosynthetic of winter wheat. The experiment included five irrigation schedules, such as no irri...A field experiment was conducted to elucidate the regulation mechanism of different irrigation schedules on population photosynthetic of winter wheat. The experiment included five irrigation schedules, such as no irrigation （W0）, irrigation once at jointing （W1j） or at booting （W1b）, irrigation twice at jointing and booting （W2）, and irrigation three times at jointing, booting and grain-filling （W3） and three planting densities, such as 180 （D1）, 300 （D2） and 450 （D3） seedlings per square meter. The results indicated that irrigation significantly improved population photosynthesis. The relationship between population photosynthesis and irrigation time/volume was to some extent parabolic. Improvements in population photosynthesis （resulting from more irrigation time/volume） were mainly related to increase in leaf area index and population light interception. Population photosynthesis exhibited a significantly negative correlation with canopy light transmittance. Population photosynthesis at grain filling stage was significantly positively correlated with dry matter accumulation at post-anthesis and grain yield. Main effects and partial correlation analysis showed that population photosynthesis of W0, W1j, W1b and W3 were regulated by canopy light transmittance and leaf area. On the other hand, population photosynthesis of W2 was mainly influenced by flag leaf photosynthetic rate. On this basis, planting 300 seedlings per square meter was the optimum combination. The combination of W2D2 increased population photosynthesis during mid-late growth stages and extended high population photosynthesis duration, which ultimately increased grain yield.展开更多
The assumption of static and deterministic conditions is common in the practice of construction project planning. However, at the construction phase, projects are subject to uncertainty. This may lead to serious sched...The assumption of static and deterministic conditions is common in the practice of construction project planning. However, at the construction phase, projects are subject to uncertainty. This may lead to serious schedule disruptions and, as a consequence, serious revisions oft.he schedule baseline. The aim of the paper is developing a method for constructing robust project schedules with a proactive procedure. Robust project scheduling allows for constructing stable schedules with time buffers introduced to cope with multiple disruptions during project execution. The method proposed by the authors, based on Monte Carlo simulation technique and mathematical programming for buffer sizing optimization, was applied to scheduling an example project. The results were compared, in terms of schedule stability, to those of the float factor heuristic procedttre.展开更多
Hospital facilities use a collection of heterogeneous devices, produced by many different vendors, to monitor the state of patient vital signs. The limited interoperability of current devices makes it difficult to syn...Hospital facilities use a collection of heterogeneous devices, produced by many different vendors, to monitor the state of patient vital signs. The limited interoperability of current devices makes it difficult to synthesize multivariate monitoring data into a unified array of real-time information regarding the patients state. Without an infrastructure for the integrated evaluation, display, and storage of vital sign data, one cannot adequately ensure that the assignment of caregivers to patients reflects the relative urgency of patient needs. This is an especially serious issue in critical care units (CCUs). We present a formal mathematical model of an operational critical care unit, together with metrics for evaluating the systematic impact of caregiver scheduling decisions on patient care. The model is rich enough to capture the essential features of device and patient diversity, and so enables us to test the hypothesis that integration of vital sign data could realistically yield a significant positive impact on the efficacy of critical care delivery outcome. To test the hypothesis, we employ the model within a computer simulation. The simulation enables us to compare the current scheduling processes in widespread use within CCUs, against a new scheduling algorithm that makes use of an integrated array of patient information collected by an (anticipated) vital sign data integration infrastructure. The simulation study provides clear evidence that such an infrastructure reduces risk to patients and lowers operational costs, and in so doing reveals the inherent costs of medical device non-interoperability.展开更多
This paper explores the influences of Emotional Regulation (ER) and work schedules on work-family conflict (WFC) among Italian nurses, also accounting for some familial variables. The data used in this study come from...This paper explores the influences of Emotional Regulation (ER) and work schedules on work-family conflict (WFC) among Italian nurses, also accounting for some familial variables. The data used in this study come from a survey conducted on 191 nurses working in two public hospitals of Tuscany (Italy). Stepwise multiple regressions were applied to examine the relationships among these variables, using the WFC as dependent variable. We found that some work related dimensions had direct effects on WFC outcomes;however, these impacts on the criterion variables are modified by the effects exerted by specific ER strategies.展开更多
The field experiment was conduced at the Agronomy Field Unit, Main Research Station, University of Agricultural Sciences, Hebbal, Bangalore, India during 2002 and 2003 to study the effect of irrigation schedules on gr...The field experiment was conduced at the Agronomy Field Unit, Main Research Station, University of Agricultural Sciences, Hebbal, Bangalore, India during 2002 and 2003 to study the effect of irrigation schedules on growth, yield and quality of baby corn. The soil of the experimental site was red sandy loam in texture with neutral reaction. The experiment was laid out in a randomized complete block design with three replications. There were seven treatments of irrigation schedules based on IW/CPE ratio of 0.6 and 1.0 during different phenophases of baby corn. The results of the experiment revealed that the baby corn dry matter was significantly higher (75.57 g.plant–1) with higher green fodder yield of 43.47 t.ha–1 due to irrigation scheduled at IW/CPE ratio of 1.0 followed by moisture stress at early stage (I3). Irrigations scheduled at IW/CPE ratio of 1.0 registered significantly higher baby corn yield of 6.60 t.ha–1 followed by the delayed irrigation at early stage of 10 - 25 DAS. Significantly higher crude protein, phosphorus, potassium and lower reducing sugars and ascorbic acid content of baby corn was recorded under IW/CPE ratio of 1.0. Delayed irrigation at 0.6 IW/CPE ratio through-out produced baby corn with higher taste and juiciness. The total crop water use ranged from 294.10 to 469.10 mm, respectively under continuously delayed irrigation at 0.6 IW/CPE ratio and frequent irrigation at IW/CPE ratio of 1.0 which also recorded higher water use efficiency.展开更多
One of the key research focuses in quantum annealing is the design and optimization of annealing schedules to enhance computational efficiency,enabling large-scale applications.QuantumZero(QZero)pioneered the integrat...One of the key research focuses in quantum annealing is the design and optimization of annealing schedules to enhance computational efficiency,enabling large-scale applications.QuantumZero(QZero)pioneered the integration of Monte Carlo Tree Search(MCTS)with neural networks to autonomously design annealing schedules within a hybrid quantum-classical framework.This approach is distinguished by its ability to enhance the performance of Monte Carlo Tree Search through the integration of neural networks,enabling the efficient design of annealing paths even with limited annealing time.The paper presents an optimized QZero method based on intuitive reasoning theory and MindSpore,which further enhances QZero’s ability to conserve computational resources and resist noise.In terms of learning efficiency,the optimized QZero algorithm improves the convergence speed of the neural network by 93%compared to the original algorithm.Notably,the average number of quantum annealing queries required to achieve 99%fidelity is reduced by 45.09%.Regarding noise resistance,the optimized QZero algorithm requires 34.27%fewer quantum annealing queries to reach 99%fidelity compared to the original algorithm.The optimized QZero algorithm demonstrates strong competitiveness in optimizing quantum annealing schedules.展开更多
European directives advocate for end-users to be aware of their energy consumption.However,individual energy monitoring tools,such as energy meters or cost allocators,are not always affordable or technically feasible ...European directives advocate for end-users to be aware of their energy consumption.However,individual energy monitoring tools,such as energy meters or cost allocators,are not always affordable or technically feasible to install.Therefore,the development of virtual tools that enable the study of energy consumption in existing buildings is necessary.Virtual sensors,particularly based on white-box models,offer the opportunity to recreate these behaviours.When calibrated with measured data,white-box models,which incorporate detailed building physics,become increasingly valuable for designing energy-efficient buildings.This research explores a novel approach to identifying building’s load period directly from energy data generated by these calibrated models.The volume of data generated by white-box models can be overwhelming for visual analysis,but the hypothesis here is that analysing this data through clustering techniques can reveal patterns related to occupant behaviour and operational schedules.By feeding indoor temperature data into the calibrated model and analysing the resulting energy outputs,the research proposes a method to identify the heating,ventilation and air conditioning(HVAC)system operation schedule,free oscillation periods and non-recurrent events.Validation is achieved by comparing the identified periods with actual measured data.This methodology enables the development of a virtual sensor for cost allocation,which minimises the need for physical sensor deployment while complying with European Union directives.The research not only demonstrates high accuracy but also the potential to outperform measured schedule.This suggests the ability of the method to identify missing sensor data or other factors affecting temperature curves,enabling fault detection and diagnostics(FDD).Consequently,this opens doors for setting optimised operation schedules that balance energy efficiency with occupant comfort.展开更多
Task scheduling in cloud computing is a multi-objective optimization problem,often involving conflicting objectives such as minimizing execution time,reducing operational cost,and maximizing resource utilization.Howev...Task scheduling in cloud computing is a multi-objective optimization problem,often involving conflicting objectives such as minimizing execution time,reducing operational cost,and maximizing resource utilization.However,traditional approaches frequently rely on single-objective optimization methods which are insufficient for capturing the complexity of such problems.To address this limitation,we introduce MDMOSA(Multi-objective Dwarf Mongoose Optimization with Simulated Annealing),a hybrid that integrates multi-objective optimization for efficient task scheduling in Infrastructure-as-a-Service(IaaS)cloud environments.MDMOSA harmonizes the exploration capabilities of the biologically inspired Dwarf Mongoose Optimization(DMO)with the exploitation strengths of Simulated Annealing(SA),achieving a balanced search process.The algorithm aims to optimize task allocation by reducing makespan and financial cost while improving system resource utilization.We evaluate MDMOSA through extensive simulations using the real-world Google Cloud Jobs(GoCJ)dataset within the CloudSim environment.Comparative analysis against benchmarked algorithms such as SMOACO,MOTSGWO,and MFPAGWO reveals that MDMOSA consistently achieves superior performance in terms of scheduling efficiency,cost-effectiveness,and scalability.These results confirm the potential of MDMOSA as a robust and adaptable solution for resource scheduling in dynamic and heterogeneous cloud computing infrastructures.展开更多
Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic effici...Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic efficiency.In this paper,aiming at the uncertainty of distributed wind power and photovoltaic output,considering the coupling relationship between power,carbon trading,and green cardmarket,the optimal operationmodel and bidding scheme of VPP in spot market,carbon trading market,and green card market are established.On this basis,through the Shapley value and independent risk contribution theory in cooperative game theory,the quantitative analysis of the total income and risk contribution of various distributed resources in the virtual power plant is realized.Moreover,the scheduling strategies of virtual power plants under different risk preferences are systematically compared,and the feasibility and accuracy of the combination of Shapley value and independent risk contribution theory in ensuring fair income distribution and reasonable risk assessment are emphasized.A comprehensive solution for virtual power plants in the multi-market environment is constructed,which integrates operation strategy,income distribution mechanism,and risk control system into a unified analysis framework.Through the simulation of multi-scenario examples,the CPLEXsolver inMATLAB software is used to optimize themodel.The proposed joint optimization scheme can increase the profit of VPP participating in carbon trading and green certificate market by 29%.The total revenue of distributed resources managed by VPP is 9%higher than that of individual participation.展开更多
In response to the challenges faced by unmanned swarms in mountain obstacle-breaching missions within complex terrains,such as poor task-resource coupling,lengthy solution generation times,and poor inter-platform coll...In response to the challenges faced by unmanned swarms in mountain obstacle-breaching missions within complex terrains,such as poor task-resource coupling,lengthy solution generation times,and poor inter-platform collaboration,an unmanned swarm scheduling strategy tailored is proposed for mountain obstacle-breaching missions.Initially,by formalizing the descriptions of obstacle breaching operations,the swarm,and obstacle targets,an optimization model is constructed with the objectives of expected global benefit,timeliness,and task completion degree.A meta-task decomposition and reassembly strategy is then introduced to more precisely match the capabilities of unmanned platforms with task requirements.Additionally,a meta-task decomposition optimization model and a meta-task allocation operator are incorporated to achieve efficient allocation of swarm resources and collaborative scheduling.Simulation results demonstrate that the model can accurately generate reasonable and feasible obstacle breaching execution plans for unmanned swarms based on specific task requirements and environmental conditions.Moreover,compared to conventional strategies,the proposed strategy enhances task completion degree and expected returns while reducing the execution time of the plans.展开更多
基金supported by the project "Quality improvement by metallurgical optimised stock temperature evolution in the reheating furnace including microstructure feedback from the rolling mill" (OPTHEAT RFSR-CT-2006-00007) of the Research Fund for Coal and Steel (RFCS) from the European Union
文摘Nowadays it is known that the thermomechanical schedules applied during hot rolling of flat products provide the steel with improved mechanical properties.In this work an optimisation tool,OptiLam (OptiLam v.1),based on a predictive software and capable of generating optimised rolling schedules to obtain the desired mechanical properties in the final product is described.OptiLam includes some well-known metallurgical models which predict microstructural evolution during hot rolling and the transformation austenite/ferrite during the cooling.Furthermore,an optimisation algorithm,which is based on the gradient method,has been added,in order to design thermomechanical sequences when a specific final grain size is desired.OptiLam has been used to optimise rolling parameters,such as strain and temperature.Here,some of the results of the software validation performed by means of hot torsion tests are presented,showing also the functionality of the tool.Finally,the application of classical optimisation models,based on the gradient method,to hot rolling operations,is also discussed.
文摘Background: The optimal dose of palliative radiotherapy (RT) in symptomatic advanced lung cancer is unclear. Patients and methods: Patients with advanced NSCLC who were indicated for thoracic palliative RT with age up to 65 y and Performance Status (PS) 0 - 2 and no significant cardiac or lung co-morbidities were randomized into two fractionation arms: arm A: 30 Gy/10 over 2 weeks and arm B: 27 Gy/6 over 3 weeks (2 fractions per week) using 2 anterior posterior (AP-PA) fields in both arms. Primary end points were symptomatic and radiological tumor response, respiratory functions assessment. Secondary end point was toxicity. Results: From December 2014 to October 2015, 40 patients were randomized, 20 patients in each arm. There was statistically insignificant higher symptomatic improvement in arm B. Four weeks after treatment, 12 out of 40 patients (30%), 6 patients in each arm, had radiological Partial Response (PR) of the primary thoracic lesion without significant difference between the two arms. There was a tendency for improvement in the post treatment mean Forced Vital Capacity (FVC) and Forced Expiratory Volume in one second (FEV1) in each arm without statistical significance. There were no reported skin reactions or esophagitis in both arms up to 4 weeks after treatment. Eleven out of the 40 patients (27.5%), 6 in arm B and 5 in arm A, had radiological signs of radiation pneumonitis without significant difference between both arms. Conclusion: The two RT fractionation schedules showed equal efficacy in terms of symptoms relief, radiological response of the primary thoracic tumor, respiratory functions and toxicity. Thus the 27 Gy/6 fractionation arm appears preferable compared to 30 Gy/10 arm to minimize the patients’ visits and load on the machines.
文摘 1. Organized and attended the Discussion on "Measures for Administration of Commercial Franchise Operations" with Ministry of Commerce in January, 2005.
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基金This work was supported by the National Natural Science Foundation of China (No. 60474002, 60504026)Shanghai Development Foundation forScience and Technology (No. 04DZ11008)
文摘Active schedule is one of the most basic and popular concepts in production scheduling research. For identical parallel machine scheduling with jobs＇ dynamic arrivals, the tight performance bounds of active schedules under the measurement of four popular objectives are respectively given in this paper. Similar analysis method and conclusions can be generalized to static identical parallel machine and single machine scheduling problem.
基金supported by a Key Projects in the National Science & Technology Pillar Program during the Eleventh Five-Year Plan Period (No.2006BAE03A08)
文摘The microstructures and mechanical properties of three X80 pipeline steel plates were investigated in this study.The plates were hot rolled by two stages, and cooled by three different cooling schedules to obtain different microstructures and mechanical properties.Transmission electron microscope（TEM） was used to observe the microstructure.The results indicated that the amount of polygonal ferrite（PF） and quasi-polygonal ferrite（QPF） decreased with decreasing of the finish cooling temperature（FCT）, while the amount and size of M-A islands were larger.Relaxation promoted the Charpy V-notch（CVN） impact toughness at-20℃, but not the drop weight tear testing（DWTT） property at-15℃, and decreased the strength of the steel.
基金Supported by the National Natural Science Foundation of China(59379407)
文摘Drip irrigation system can achieve high uniformity. When the system is designed for uniformity coefficient equal or more than 70%, the water application in the field can be expressed as a normal distribution and further simplified to a linear distribution. This paper will describe the irrigation scheduling parameters, percent of deficit, application efficiency and coefficient of variation by simple mathematical model. Using this effective model and the irrigation application, the total yield affected by the total water application for different uniformity of irrigation application can be determined. More over, this paper uses the cost of water, price of yield, uniformity of the drip irrigation system, crop response to water application and environmental concerns of pollution and contamination to determine the optimal irrigation schedule. A case study shows that the optimal irrigation schedule can achieve the effect of water saving and production increment compared with the conventional irrigation schedule in which the whole field is fully irrigated.
基金Funded by the Science Research Program of Hebei Province under Grant No. 2002135.
文摘To minimize the deviations of the net present values of project payment for both the owner and the client and optimize project payment schedules, a Nash equilibrium model based on game theory was set up and a genetic algorithm was developed to work out the Nash equilibrium solution with a two-stage backward inductive approach that requires the client responds to the owner’s payment schedule with an activity schedule so as to maximize the client’s net present value of cash flows. A case study demonstrated that a payment schedule at the Nash equilibrium position enables both the owner and the client to gain their desirable interests, thus is a win-win solution for both parties. Despite the computation time of the proposed algrithm in need of improving, combining Nash equilibrium and genetic algorithm into a complete-information dynamic-game model is a promising method for project management optimization.
文摘The increased concern over global climate change and lack of long-term sustainability of fossil fuels in the projected future has prompted further research into advanced alternative fuel vehicles to reduce vehicle emissions and fuel consumption. One of the primary advanced vehicle research areas involves electrification and hybridization of vehicles. As hybrid-electric vehicle technology has advanced, so has the need for more innovative control schemes for hybrid vehicles, including the development and optimization of hybrid powertrain transmission shift schedules. The hybrid shift schedule works in tandem with a cost function-based torque split algorithm that dynamically determines the optimal torque command for the electric motor and engine. The focus of this work is to develop and analyze the benefits and limitations of two different shift schedules for a position-3 (P3) parallel hybrid-electric vehicle. a traditional two-parameter shift schedule that operates as a function of vehicle accelerator position and vehicle speed (state of charge (SOC) independent shift schedule), and a three-parameter shift schedule that also adapts to fluctuations in the state of charge of the high voltage batteries (SOC dependent shift schedule). The shift schedules were generated using an exhaustive search coupled with a fitness function to evaluate all possible vehicle operating points. The generated shift schedules were then tested in the software-in-the-loop (SIL) environment and the vehicle-in-the-loop (VIL) environment and compared to each other, as well as to the stock 8L45 8-speed transmission shift schedule. The results show that both generated shift schedules improved upon the stock transmission shift schedule used in the hybrid powertrain comparing component efficiency, vehicle efficiency, engine fuel economy, and vehicle fuel economy.
文摘Two problems for task schedules in a multiprocessor parallel system are discussed in Ans paper (1) given a partially ordered set of tasks represented by the venices of an acyclic directed graph with their corresponding processing bines, derive the lower bound on the Annimum time(LBMT) needed to process the task graph for a given number of processors. (2) Determine the lower bound on minimum number of processors(LBMP) needed to complete those tasks in minimum bine. It is shown that the proposed LBMT is sharper than previously Known values and the comPUtational aspeCts of these bounds are also discussed.
基金Supported by China and CAS Main Direction Program of Knowledge Innovation (KSCX2-EW-B-1)China and CAS Knowledge Innovation Project(KSCX1-YW-09-06)
文摘A field experiment was conducted to elucidate the regulation mechanism of different irrigation schedules on population photosynthetic of winter wheat. The experiment included five irrigation schedules, such as no irrigation （W0）, irrigation once at jointing （W1j） or at booting （W1b）, irrigation twice at jointing and booting （W2）, and irrigation three times at jointing, booting and grain-filling （W3） and three planting densities, such as 180 （D1）, 300 （D2） and 450 （D3） seedlings per square meter. The results indicated that irrigation significantly improved population photosynthesis. The relationship between population photosynthesis and irrigation time/volume was to some extent parabolic. Improvements in population photosynthesis （resulting from more irrigation time/volume） were mainly related to increase in leaf area index and population light interception. Population photosynthesis exhibited a significantly negative correlation with canopy light transmittance. Population photosynthesis at grain filling stage was significantly positively correlated with dry matter accumulation at post-anthesis and grain yield. Main effects and partial correlation analysis showed that population photosynthesis of W0, W1j, W1b and W3 were regulated by canopy light transmittance and leaf area. On the other hand, population photosynthesis of W2 was mainly influenced by flag leaf photosynthetic rate. On this basis, planting 300 seedlings per square meter was the optimum combination. The combination of W2D2 increased population photosynthesis during mid-late growth stages and extended high population photosynthesis duration, which ultimately increased grain yield.
文摘The assumption of static and deterministic conditions is common in the practice of construction project planning. However, at the construction phase, projects are subject to uncertainty. This may lead to serious schedule disruptions and, as a consequence, serious revisions oft.he schedule baseline. The aim of the paper is developing a method for constructing robust project schedules with a proactive procedure. Robust project scheduling allows for constructing stable schedules with time buffers introduced to cope with multiple disruptions during project execution. The method proposed by the authors, based on Monte Carlo simulation technique and mathematical programming for buffer sizing optimization, was applied to scheduling an example project. The results were compared, in terms of schedule stability, to those of the float factor heuristic procedttre.
文摘Hospital facilities use a collection of heterogeneous devices, produced by many different vendors, to monitor the state of patient vital signs. The limited interoperability of current devices makes it difficult to synthesize multivariate monitoring data into a unified array of real-time information regarding the patients state. Without an infrastructure for the integrated evaluation, display, and storage of vital sign data, one cannot adequately ensure that the assignment of caregivers to patients reflects the relative urgency of patient needs. This is an especially serious issue in critical care units (CCUs). We present a formal mathematical model of an operational critical care unit, together with metrics for evaluating the systematic impact of caregiver scheduling decisions on patient care. The model is rich enough to capture the essential features of device and patient diversity, and so enables us to test the hypothesis that integration of vital sign data could realistically yield a significant positive impact on the efficacy of critical care delivery outcome. To test the hypothesis, we employ the model within a computer simulation. The simulation enables us to compare the current scheduling processes in widespread use within CCUs, against a new scheduling algorithm that makes use of an integrated array of patient information collected by an (anticipated) vital sign data integration infrastructure. The simulation study provides clear evidence that such an infrastructure reduces risk to patients and lowers operational costs, and in so doing reveals the inherent costs of medical device non-interoperability.
文摘This paper explores the influences of Emotional Regulation (ER) and work schedules on work-family conflict (WFC) among Italian nurses, also accounting for some familial variables. The data used in this study come from a survey conducted on 191 nurses working in two public hospitals of Tuscany (Italy). Stepwise multiple regressions were applied to examine the relationships among these variables, using the WFC as dependent variable. We found that some work related dimensions had direct effects on WFC outcomes;however, these impacts on the criterion variables are modified by the effects exerted by specific ER strategies.
文摘The field experiment was conduced at the Agronomy Field Unit, Main Research Station, University of Agricultural Sciences, Hebbal, Bangalore, India during 2002 and 2003 to study the effect of irrigation schedules on growth, yield and quality of baby corn. The soil of the experimental site was red sandy loam in texture with neutral reaction. The experiment was laid out in a randomized complete block design with three replications. There were seven treatments of irrigation schedules based on IW/CPE ratio of 0.6 and 1.0 during different phenophases of baby corn. The results of the experiment revealed that the baby corn dry matter was significantly higher (75.57 g.plant–1) with higher green fodder yield of 43.47 t.ha–1 due to irrigation scheduled at IW/CPE ratio of 1.0 followed by moisture stress at early stage (I3). Irrigations scheduled at IW/CPE ratio of 1.0 registered significantly higher baby corn yield of 6.60 t.ha–1 followed by the delayed irrigation at early stage of 10 - 25 DAS. Significantly higher crude protein, phosphorus, potassium and lower reducing sugars and ascorbic acid content of baby corn was recorded under IW/CPE ratio of 1.0. Delayed irrigation at 0.6 IW/CPE ratio through-out produced baby corn with higher taste and juiciness. The total crop water use ranged from 294.10 to 469.10 mm, respectively under continuously delayed irrigation at 0.6 IW/CPE ratio and frequent irrigation at IW/CPE ratio of 1.0 which also recorded higher water use efficiency.
基金supported by the Defense Innovation Special Zone Project and CAAI-Huawei MindSpore Open Fund.
文摘One of the key research focuses in quantum annealing is the design and optimization of annealing schedules to enhance computational efficiency,enabling large-scale applications.QuantumZero(QZero)pioneered the integration of Monte Carlo Tree Search(MCTS)with neural networks to autonomously design annealing schedules within a hybrid quantum-classical framework.This approach is distinguished by its ability to enhance the performance of Monte Carlo Tree Search through the integration of neural networks,enabling the efficient design of annealing paths even with limited annealing time.The paper presents an optimized QZero method based on intuitive reasoning theory and MindSpore,which further enhances QZero’s ability to conserve computational resources and resist noise.In terms of learning efficiency,the optimized QZero algorithm improves the convergence speed of the neural network by 93%compared to the original algorithm.Notably,the average number of quantum annealing queries required to achieve 99%fidelity is reduced by 45.09%.Regarding noise resistance,the optimized QZero algorithm requires 34.27%fewer quantum annealing queries to reach 99%fidelity compared to the original algorithm.The optimized QZero algorithm demonstrates strong competitiveness in optimizing quantum annealing schedules.
基金funded by the Catedra Sanitas de Salud y Medio Ambiente of Universidad de Navarrafunded by the Agencia Estatal de Investigatión under the project“Gemelo Digital de Nueva Generatión de Edificios Inteligentes”(DigiTwin)(ref.CPP2021-008909).
文摘European directives advocate for end-users to be aware of their energy consumption.However,individual energy monitoring tools,such as energy meters or cost allocators,are not always affordable or technically feasible to install.Therefore,the development of virtual tools that enable the study of energy consumption in existing buildings is necessary.Virtual sensors,particularly based on white-box models,offer the opportunity to recreate these behaviours.When calibrated with measured data,white-box models,which incorporate detailed building physics,become increasingly valuable for designing energy-efficient buildings.This research explores a novel approach to identifying building’s load period directly from energy data generated by these calibrated models.The volume of data generated by white-box models can be overwhelming for visual analysis,but the hypothesis here is that analysing this data through clustering techniques can reveal patterns related to occupant behaviour and operational schedules.By feeding indoor temperature data into the calibrated model and analysing the resulting energy outputs,the research proposes a method to identify the heating,ventilation and air conditioning(HVAC)system operation schedule,free oscillation periods and non-recurrent events.Validation is achieved by comparing the identified periods with actual measured data.This methodology enables the development of a virtual sensor for cost allocation,which minimises the need for physical sensor deployment while complying with European Union directives.The research not only demonstrates high accuracy but also the potential to outperform measured schedule.This suggests the ability of the method to identify missing sensor data or other factors affecting temperature curves,enabling fault detection and diagnostics(FDD).Consequently,this opens doors for setting optimised operation schedules that balance energy efficiency with occupant comfort.
文摘Task scheduling in cloud computing is a multi-objective optimization problem,often involving conflicting objectives such as minimizing execution time,reducing operational cost,and maximizing resource utilization.However,traditional approaches frequently rely on single-objective optimization methods which are insufficient for capturing the complexity of such problems.To address this limitation,we introduce MDMOSA(Multi-objective Dwarf Mongoose Optimization with Simulated Annealing),a hybrid that integrates multi-objective optimization for efficient task scheduling in Infrastructure-as-a-Service(IaaS)cloud environments.MDMOSA harmonizes the exploration capabilities of the biologically inspired Dwarf Mongoose Optimization(DMO)with the exploitation strengths of Simulated Annealing(SA),achieving a balanced search process.The algorithm aims to optimize task allocation by reducing makespan and financial cost while improving system resource utilization.We evaluate MDMOSA through extensive simulations using the real-world Google Cloud Jobs(GoCJ)dataset within the CloudSim environment.Comparative analysis against benchmarked algorithms such as SMOACO,MOTSGWO,and MFPAGWO reveals that MDMOSA consistently achieves superior performance in terms of scheduling efficiency,cost-effectiveness,and scalability.These results confirm the potential of MDMOSA as a robust and adaptable solution for resource scheduling in dynamic and heterogeneous cloud computing infrastructures.
基金funded by the Department of Education of Liaoning Province and was supported by the Basic Scientific Research Project of the Department of Education of Liaoning Province(Grant No.LJ222411632051)and(Grant No.LJKQZ2021085)Natural Science Foundation Project of Liaoning Province(Grant No.2022-BS-222).
文摘Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic efficiency.In this paper,aiming at the uncertainty of distributed wind power and photovoltaic output,considering the coupling relationship between power,carbon trading,and green cardmarket,the optimal operationmodel and bidding scheme of VPP in spot market,carbon trading market,and green card market are established.On this basis,through the Shapley value and independent risk contribution theory in cooperative game theory,the quantitative analysis of the total income and risk contribution of various distributed resources in the virtual power plant is realized.Moreover,the scheduling strategies of virtual power plants under different risk preferences are systematically compared,and the feasibility and accuracy of the combination of Shapley value and independent risk contribution theory in ensuring fair income distribution and reasonable risk assessment are emphasized.A comprehensive solution for virtual power plants in the multi-market environment is constructed,which integrates operation strategy,income distribution mechanism,and risk control system into a unified analysis framework.Through the simulation of multi-scenario examples,the CPLEXsolver inMATLAB software is used to optimize themodel.The proposed joint optimization scheme can increase the profit of VPP participating in carbon trading and green certificate market by 29%.The total revenue of distributed resources managed by VPP is 9%higher than that of individual participation.
基金supported by the National Natural Science Foundation of China(61374186)。
文摘In response to the challenges faced by unmanned swarms in mountain obstacle-breaching missions within complex terrains,such as poor task-resource coupling,lengthy solution generation times,and poor inter-platform collaboration,an unmanned swarm scheduling strategy tailored is proposed for mountain obstacle-breaching missions.Initially,by formalizing the descriptions of obstacle breaching operations,the swarm,and obstacle targets,an optimization model is constructed with the objectives of expected global benefit,timeliness,and task completion degree.A meta-task decomposition and reassembly strategy is then introduced to more precisely match the capabilities of unmanned platforms with task requirements.Additionally,a meta-task decomposition optimization model and a meta-task allocation operator are incorporated to achieve efficient allocation of swarm resources and collaborative scheduling.Simulation results demonstrate that the model can accurately generate reasonable and feasible obstacle breaching execution plans for unmanned swarms based on specific task requirements and environmental conditions.Moreover,compared to conventional strategies,the proposed strategy enhances task completion degree and expected returns while reducing the execution time of the plans.
