Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been...Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling problems.However,HHO suffers from premature convergence when solving NP-hard problems.Therefore,this paper proposes an improved HHO algorithm(GNHHO)to solve the FJSP.GNHHO introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the makespan.This paper chooses a two-segment encoding mode based on the job and the machine of the FJSP.To verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard FJSPs.Besides,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s FJSP.The optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic scheduling.Moreover,it achieves an average increase of 21.50%in the on-time order delivery rate.The results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.展开更多
The number of tardy jobs of the single machine scheduling problem with a variable processing time is studied in accordance with the published instances of traffic transportation management engineering. It is proved ...The number of tardy jobs of the single machine scheduling problem with a variable processing time is studied in accordance with the published instances of traffic transportation management engineering. It is proved by 3 partition problem that if the problem is of ready time and common deadline constrained, its complexity is NP hard in the strong sense. Finally, a polynomial algorithm for solving unit processing time and common deadline problems is proposed.展开更多
The photodissociation dynamics of 2-iodotoluene following excitation at 266 nm have been investigated employing femtosecond time-resolved mass spectrometry. The photofragments are detected by multiphoton ionization us...The photodissociation dynamics of 2-iodotoluene following excitation at 266 nm have been investigated employing femtosecond time-resolved mass spectrometry. The photofragments are detected by multiphoton ionization using an intense laser field centered at 800 nm. A dissociation time of 3804-50 fs was measured from the rising time of the co-fragments of toluene radical （C7H7） and iodine atom （I）, which is attributed to the averaged time needed for the C-I bond breaking for the simultaneously excited nσ and ππ＊ states by 266 nm pump light. In addition, a probe light centered at 298.23 nm corresponding to resonance wavelength of ground-state iodine atom is used to selectively ionize ground-state iodine atoms generated from the dissociation of initially populated hσ＊ and ππ＊ states. And a rise time of 4004-50 fs is extracted from the fitting of time-dependent I＋ transient, which is in agreement with the dissociation time obtained by multiphoton ionization with 800 nm, suggesting that the main dissociative products are ground-state iodine atoms.展开更多
Recently, canopy transpiration （Ec） has been often estimated by xylem sap-flow measurements. However, there is a significant time lag between sap flow measured at the base of the stem and canopy transpiration due to...Recently, canopy transpiration （Ec） has been often estimated by xylem sap-flow measurements. However, there is a significant time lag between sap flow measured at the base of the stem and canopy transpiration due to the capacitive exchange between the transpiration stream and stem water storage. Significant errors will be introduced in canopy conductance （gc） and canopy transpiration estimation if the time lag is neglected. In this study, a cross-correlation analysis was used to quantify the time lag, and the sap flowbased transpiration was measured to pararneterize Jarvistype models of gc and thus to simulate Ec of Populus cathayana using the Penman-Monteith equation. The results indicate that solar radiation （Rs） and vapor pressure deficit （VPD） are not fully coincident with sap flow and have an obvious lag effect; the sap flow lags behind Rs and precedes VPD, and there is a 1-h time shift between Eo and sap flow in the 30-min interval data set. A parameterized Jarvis-type gc model is suitable to predict P. cathayana transpiration and explains more than 80% of the variation observed in go, and the relative error was less than 25%, which shows a preferable simulation effect. The root mean square error （RMSEs） between the predicted and measured Ec were 1.91×10^-3 （with the time lag） and 3.12×10^-3cm h^-1 （without the time lag）. More importantly, Ec simulation precision that incorporates time lag is improved by 6% compared to the results without the time lag, with the mean relative error （MRE） of only 8.32% and the mean absolute error （MAE） of 1.48 × 10^-3 cm h^-1.展开更多
Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with...Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.展开更多
Firstly an overview of the potential impact on work-in-process （WIP） and lead time is provided when transfer lot sizes are undifferentiated from processing lot sizes. Simple performance examples are compared to thos...Firstly an overview of the potential impact on work-in-process （WIP） and lead time is provided when transfer lot sizes are undifferentiated from processing lot sizes. Simple performance examples are compared to those from a shop with one-piece transfer lots. Next, a mathematical programming model for minimizing lead time in the mixed-model job shop is presented, in which one-piece transfer lots are used. Key factors affecting lead time are found by analyzing the sum of the longest setup time of individual items among the shared processes （SLST） and the longest processing time of individual items among processes （LPT）. And lead time can be minimized by cutting down the SLST and LPT. Reduction of the SLST is described as a traveling salesman problem （TSP）, and the minimum of the SLST is solved through job shop scheduling. Removing the bottleneck and leveling the production line optimize the LPT. If the number of items produced is small, the routings are relatively short, and items and facilities are changed infrequently, the optimal schedule will remain valid. Finally a brief example serves to illustrate the method.展开更多
In this article,a high-order scheme,which is formulated by combining the quadratic finite element method in space with a second-order time discrete scheme,is developed for looking for the numerical solution of a two-d...In this article,a high-order scheme,which is formulated by combining the quadratic finite element method in space with a second-order time discrete scheme,is developed for looking for the numerical solution of a two-dimensional nonlinear time fractional thermal diffusion model.The time Caputo fractional derivative is approximated by using the L2-1formula,the first-order derivative and nonlinear term are discretized by some second-order approximation formulas,and the quadratic finite element is used to approximate the spatial direction.The error accuracy O(h3+t2)is obtained,which is verified by the numerical results.展开更多
It is generally known that the solutions of deterministic and stochastic differential equations （SDEs） usually grow linearly at such a rate that they may become unbounded after a small lapse of time and may eventual...It is generally known that the solutions of deterministic and stochastic differential equations （SDEs） usually grow linearly at such a rate that they may become unbounded after a small lapse of time and may eventually blow up or explode in finite time. If the drift and diffusion functions are globally Lipschitz, linear growth may still be experienced, as well as a possible blow-up of solutions in finite time. In this paper, a nonlinear scalar delay differential equation with a constant time lag is perturbed by a multiplicative Ito-type time - space white noise to form a stochastic Fokker-Planck delay differential equation. It is established that no explosion is possible in the presence of any intrinsically slow time - space white noise of Ito - type as manifested in the resulting stochastic Fokker- Planck delay differential equation. Time - space white noise has a role to play since the solution of the classical nonlinear equation without it still exhibits explosion.展开更多
文摘Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling problems.However,HHO suffers from premature convergence when solving NP-hard problems.Therefore,this paper proposes an improved HHO algorithm(GNHHO)to solve the FJSP.GNHHO introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the makespan.This paper chooses a two-segment encoding mode based on the job and the machine of the FJSP.To verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard FJSPs.Besides,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s FJSP.The optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic scheduling.Moreover,it achieves an average increase of 21.50%in the on-time order delivery rate.The results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.
文摘The number of tardy jobs of the single machine scheduling problem with a variable processing time is studied in accordance with the published instances of traffic transportation management engineering. It is proved by 3 partition problem that if the problem is of ready time and common deadline constrained, its complexity is NP hard in the strong sense. Finally, a polynomial algorithm for solving unit processing time and common deadline problems is proposed.
基金This work was supported by the National Basic Research Program of China （973 Program） （No.2013CB922200） and the National Natural Science Foundation of China （No.91121006, No.21273274, No.21173256, and No.21303255）.
文摘The photodissociation dynamics of 2-iodotoluene following excitation at 266 nm have been investigated employing femtosecond time-resolved mass spectrometry. The photofragments are detected by multiphoton ionization using an intense laser field centered at 800 nm. A dissociation time of 3804-50 fs was measured from the rising time of the co-fragments of toluene radical （C7H7） and iodine atom （I）, which is attributed to the averaged time needed for the C-I bond breaking for the simultaneously excited nσ and ππ＊ states by 266 nm pump light. In addition, a probe light centered at 298.23 nm corresponding to resonance wavelength of ground-state iodine atom is used to selectively ionize ground-state iodine atoms generated from the dissociation of initially populated hσ＊ and ππ＊ states. And a rise time of 4004-50 fs is extracted from the fitting of time-dependent I＋ transient, which is in agreement with the dissociation time obtained by multiphoton ionization with 800 nm, suggesting that the main dissociative products are ground-state iodine atoms.
基金supported by the Qinghai province natural science foundation project(2015-ZJ-902)the Qinghai province science and technology plan program(2014-NK-A4-4)
文摘Recently, canopy transpiration （Ec） has been often estimated by xylem sap-flow measurements. However, there is a significant time lag between sap flow measured at the base of the stem and canopy transpiration due to the capacitive exchange between the transpiration stream and stem water storage. Significant errors will be introduced in canopy conductance （gc） and canopy transpiration estimation if the time lag is neglected. In this study, a cross-correlation analysis was used to quantify the time lag, and the sap flowbased transpiration was measured to pararneterize Jarvistype models of gc and thus to simulate Ec of Populus cathayana using the Penman-Monteith equation. The results indicate that solar radiation （Rs） and vapor pressure deficit （VPD） are not fully coincident with sap flow and have an obvious lag effect; the sap flow lags behind Rs and precedes VPD, and there is a 1-h time shift between Eo and sap flow in the 30-min interval data set. A parameterized Jarvis-type gc model is suitable to predict P. cathayana transpiration and explains more than 80% of the variation observed in go, and the relative error was less than 25%, which shows a preferable simulation effect. The root mean square error （RMSEs） between the predicted and measured Ec were 1.91×10^-3 （with the time lag） and 3.12×10^-3cm h^-1 （without the time lag）. More importantly, Ec simulation precision that incorporates time lag is improved by 6% compared to the results without the time lag, with the mean relative error （MRE） of only 8.32% and the mean absolute error （MAE） of 1.48 × 10^-3 cm h^-1.
基金supported by the National Natural Science Foundation (71301119)the Shanghai Natural Science Foundation (12ZR1434100)
文摘Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.
基金This project is supported by National Natural Science Foundation of China (No.70372062, No.70572044)Program for New Century Excellent Talents in University of China (No.NCET-04-0240).
文摘Firstly an overview of the potential impact on work-in-process （WIP） and lead time is provided when transfer lot sizes are undifferentiated from processing lot sizes. Simple performance examples are compared to those from a shop with one-piece transfer lots. Next, a mathematical programming model for minimizing lead time in the mixed-model job shop is presented, in which one-piece transfer lots are used. Key factors affecting lead time are found by analyzing the sum of the longest setup time of individual items among the shared processes （SLST） and the longest processing time of individual items among processes （LPT）. And lead time can be minimized by cutting down the SLST and LPT. Reduction of the SLST is described as a traveling salesman problem （TSP）, and the minimum of the SLST is solved through job shop scheduling. Removing the bottleneck and leveling the production line optimize the LPT. If the number of items produced is small, the routings are relatively short, and items and facilities are changed infrequently, the optimal schedule will remain valid. Finally a brief example serves to illustrate the method.
基金the National Natural Science Fund(11661058,11761053)Natural Science Fund of Inner Mongolia Autonomous Region(2016MS0102,2017MS0107)+1 种基金Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(NJYT-17-A07)National Undergraduate Innovative Training Project of Inner Mongolia University(201710126026).
文摘In this article,a high-order scheme,which is formulated by combining the quadratic finite element method in space with a second-order time discrete scheme,is developed for looking for the numerical solution of a two-dimensional nonlinear time fractional thermal diffusion model.The time Caputo fractional derivative is approximated by using the L2-1formula,the first-order derivative and nonlinear term are discretized by some second-order approximation formulas,and the quadratic finite element is used to approximate the spatial direction.The error accuracy O(h3+t2)is obtained,which is verified by the numerical results.
文摘It is generally known that the solutions of deterministic and stochastic differential equations （SDEs） usually grow linearly at such a rate that they may become unbounded after a small lapse of time and may eventually blow up or explode in finite time. If the drift and diffusion functions are globally Lipschitz, linear growth may still be experienced, as well as a possible blow-up of solutions in finite time. In this paper, a nonlinear scalar delay differential equation with a constant time lag is perturbed by a multiplicative Ito-type time - space white noise to form a stochastic Fokker-Planck delay differential equation. It is established that no explosion is possible in the presence of any intrinsically slow time - space white noise of Ito - type as manifested in the resulting stochastic Fokker- Planck delay differential equation. Time - space white noise has a role to play since the solution of the classical nonlinear equation without it still exhibits explosion.
