A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Se...A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Secondly, an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity. Thirdly, based on the idea of iterated greedy algorithm, some newly designed schemes for employed bee, onlooker bee and scout bee are presented. The performance of the proposed algorithm is tested on the well-known Taillard benchmark set, and the computational results demonstrate the effectiveness of the discrete artificial bee colony algorithm. In addition, the best known solutions of the benchmark set are provided for the blocking flow shop scheduling problem with total flow time criterion.展开更多
To solve the scheduling problem of dual-armed cluster tools for wafer fabrications with residency time and reentrant constraints,a heuristic scheduling algorithm was developed.Firstly,on the basis of formulating sched...To solve the scheduling problem of dual-armed cluster tools for wafer fabrications with residency time and reentrant constraints,a heuristic scheduling algorithm was developed.Firstly,on the basis of formulating scheduling problems domain of dual-armed cluster tools,a non-integer programming model was set up with a minimizing objective function of the makespan.Combining characteristics of residency time and reentrant constraints,a scheduling algorithm of searching the optimal operation path of dual-armed transport module was presented under many kinds of robotic scheduling paths for dual-armed cluster tools.Finally,the experiments were designed to evaluate the proposed algorithm.The results show that the proposed algorithm is feasible and efficient for obtaining an optimal scheduling solution of dual-armed cluster tools with residency time and reentrant constraints.展开更多
A class of nonidentical parallel machine scheduling problems are considered in which the goal is to minimize the total weighted completion time. Models and relaxations are collected. Most of these problems are NP-hard...A class of nonidentical parallel machine scheduling problems are considered in which the goal is to minimize the total weighted completion time. Models and relaxations are collected. Most of these problems are NP-hard, in the strong sense, or open problems, therefore approximation algorithms are studied. The review reveals that there exist some potential areas worthy of further research.展开更多
With the development of rapid-response Earth-observing techniques, the demand for reducing a requirements-tasking-effects cycle from 1 day to hours grows rapidly. For instance, a satellite user always wants to receive...With the development of rapid-response Earth-observing techniques, the demand for reducing a requirements-tasking-effects cycle from 1 day to hours grows rapidly. For instance, a satellite user always wants to receive requested data in near real-time to support their urgent mis- sions, such as dealing with wildfires, volcanoes, flooding events, etc. In this paper, we try to reduce data transmission time for achieving this goal. The new feature of a responsive satellite is that users can receive signals from it directly. Therefore, the traditional satellite control and operational tech- niques need to be improved to accommodate these changes in user needs and technical upgrading. With that in mind, a data transmission topological model is constructed. Based on this model, we can deal with the satellite data transmission problem as a multi-constraint and multi-objective path- scheduling problem. However, there are many optional data transmission paths for each target based on this model, and the shortest path is preferred. In addition, satellites represent scarce resources that must be carefully scheduled in order to satisfy as many consumer requests as possible. To efficiently balance response time and resource utilization, a K-shortest path genetic algorithm is proposed for solving the data transmission problem. Simulations and analysis show the feasibility and the adaptability of the proposed approach.展开更多
In present era, one of the most important resources of computer machine is CPU. With the increasing number of application, there exist a large number of processes in the computer system at the same time. Many processe...In present era, one of the most important resources of computer machine is CPU. With the increasing number of application, there exist a large number of processes in the computer system at the same time. Many processes in system simultaneously raise a challenging circumstance of managing the CPU in such a manner that the CPU utilization and processes execution gets optimal performance. The world is still waiting for most efficient algorithm which remains a challenging issue. In this manuscript, we have proposed a new algorithm Progressively Varying Response Ratio Priority a preemptive CPU scheduling algorithm based on the Priority Algorithm and Shortest Remaining Time First. In this scheduling algorithm, the priority is been calculated and the processes with high priority get CPU first or next. For new process, the priority of it becomes equal to inverse of burst time and for the old processes the priority calculation takes place as a ratio of waiting time and remaining burst time. The objective is to get all the processes executed with minimum average waiting time and no starvation. Experiment and comparison show that the VRRP outperforms other CPU scheduling algorithms. It gives better evaluation results in the form of scheduling criteria. We have used the deterministic model to compare the different algorithms.展开更多
Motivated by industrial applications we study a single-machine scheduling problem in which all the jobs are mutu-ally independent and available at time zero.The machine processes the jobs sequentially and it is not id...Motivated by industrial applications we study a single-machine scheduling problem in which all the jobs are mutu-ally independent and available at time zero.The machine processes the jobs sequentially and it is not idle if there is any job to be pro-cessed.The operation of each job cannot be interrupted.The machine cannot process more than one job at a time.A setup time is needed if the machine switches from one type of job to another.The objective is to find an optimal schedule with the minimal total jobs’completion time.While the sum of jobs’processing time is always a constant,the objective is to minimize the sum of setup times.Ant colony optimization(ACO)is a meta-heuristic that has recently been applied to scheduling problem.In this paper we propose an improved ACO-Branching Ant Colony with Dynamic Perturbation(DPBAC)algorithm for the single-machine schedul-ing problem.DPBAC improves traditional ACO in following aspects:introducing Branching Method to choose starting points;im-proving state transition rules;introducing Mutation Method to shorten tours;improving pheromone updating rules and introduc-ing Conditional Dynamic Perturbation Strategy.Computational results show that DPBAC algorithm is superior to the traditional ACO algorithm.展开更多
In this paper, by considering the fuzzy nature of the data in real-life problems, single machine scheduling problems with fuzzy processing time and multiple objectives are formulated and an efficient genetic algorithm...In this paper, by considering the fuzzy nature of the data in real-life problems, single machine scheduling problems with fuzzy processing time and multiple objectives are formulated and an efficient genetic algorithm which is suitable for solving these problems is proposed. As illustrative numerical examples, twenty jobs processing on a machine is considered. The feasibility and effectiveness of the proposed method have been demonstrated in the simulation.展开更多
Dynamic exclusive pickup and delivery problem with time windows (DE-PDPTW), aspecial dynamic vehicle scheduling problem, is proposed. Its mathematical description is given andits static properties are analyzed, and th...Dynamic exclusive pickup and delivery problem with time windows (DE-PDPTW), aspecial dynamic vehicle scheduling problem, is proposed. Its mathematical description is given andits static properties are analyzed, and then the problem is simplified asthe asymmetrical travelingsalesman problem with time windows. The rolling horizon scheduling algorithm (RHSA) to solve thisdynamic problem is proposed. By the rolling of time horizon, the RHSA can adapt to the problem'sdynamic change and reduce the computation time by dealing with only part of the customers in eachrolling time horizon. Then, its three factors, the current customer window, the scheduling of thecurrent customer window and the rolling strategy, are analyzed. The test results demonstrate theeffectiveness of the RHSA to solve the dynamic vehicle scheduling problem.展开更多
Lot scheduling problem with idle time transfer between processes to minimize mean flow time is very important because to minimize mean flow time is to minimize work in process. But the problem is NP hard and no polyn...Lot scheduling problem with idle time transfer between processes to minimize mean flow time is very important because to minimize mean flow time is to minimize work in process. But the problem is NP hard and no polynomial algorithm exists to guarantee optimal solution. Based the analysis the mathematical structure of the problem, the paper presents a new heuristic algorithm. Computer simulation shows that the proposed heuristic algorithm performs well in terms of both quality of solution and execution speed.展开更多
It is of great significance to carry out effective scheduling for the carrier-based aircraft flight deck operations.In this paper,the precedence constraints and resource constraints in flight deck operations are analy...It is of great significance to carry out effective scheduling for the carrier-based aircraft flight deck operations.In this paper,the precedence constraints and resource constraints in flight deck operations are analyzed,then the model of the multi-aircraft integrated scheduling problem with transfer times(MAISPTT)is established.A dual population multi-operator genetic algorithm(DPMOGA)is proposed for solving the problem.In the algorithm,the dual population structure and random-key encoding modified by starting/ending time of operations are adopted,and multiple genetic operators are self-adaptively used to obtain better encodings.In order to conduct the mapping from encodings to feasible schedules,serial and parallel scheduling generation scheme-based decoding operators,each of which adopts different justified mechanisms in two separated populations,are introduced.The superiority of the DPMOGA is verified by simulation experiments.展开更多
In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its s...In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.展开更多
Support vehicles are part of the main body of airport ground operations,and their scheduling efficiency directly impacts flight delays.A mathematical model is constructed and the responsiveness of support vehicles for...Support vehicles are part of the main body of airport ground operations,and their scheduling efficiency directly impacts flight delays.A mathematical model is constructed and the responsiveness of support vehicles for current operational demands is proposed to study optimization algorithms for vehicle scheduling.The model is based on the constraint relationship of the initial operation time,time window,and gate position distribution,which gives an improvement to the ant colony algorithm(ACO).The impacts of the improved ACO as used for support vehicle optimization are compared and analyzed.The results show that the scheduling scheme of refueling trucks based on the improved ACO can reduce flight delays caused by refueling operations by 56.87%,indicating the improved ACO can improve support vehicle scheduling.Besides,the improved ACO can jump out of local optima,which can balance the working time of refueling trucks.This research optimizes the scheduling scheme of support vehicles under the existing conditions of airports,which has practical significance to fully utilize ground service resources,improve the efficiency of airport ground operations,and effectively reduce flight delays caused by ground service support.展开更多
We put forward an optimal disk schedule with n disk requests and prove its optimality mathematically.Generalizing the idea of an optimal disk schedule, we remove the limit of n requests and, at the same time, consider...We put forward an optimal disk schedule with n disk requests and prove its optimality mathematically.Generalizing the idea of an optimal disk schedule, we remove the limit of n requests and, at the same time, consider the dynamically arrival model of disk requests to obtain an algorithm, shortest path first-fit first （SPFF）. This algorithm is based on the shortest path of disk head motion constructed by all the pendent requests. From view of the head moving distance, it has the stronger glohality than SSTF. From view of the head-moving direction, it has the better flexibility than SCAN. Therefore, SPFF keeps the advantage of SCAN and, at the same time, absorbs the strength of SSTF. The algorithm SPFF not only shows the more superiority than other scheduling polices, but also have higher adjustability to meet the computer system＇s different demands.展开更多
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
Power generation dispatching is a large complex system problem with multi-dimensional and nonlinear characteristics. A mathematical model was established based on the principle of reservoir operation. A large quantity...Power generation dispatching is a large complex system problem with multi-dimensional and nonlinear characteristics. A mathematical model was established based on the principle of reservoir operation. A large quantity of optimal scheduling processes were obtained by calculating the daily runoff process within three typical years, and a large number of simulated daily runoff processes were obtained using the progressive optimality algorithm （POA） in combination with the genetic algorithm （GA）. After analyzing the optimal scheduling processes, the corresponding scheduling rules were determined, and the practical formulas were obtained. These rules can make full use of the rolling runoff forecast and carry out the rolling scheduling. Compared with the optimized results, the maximum relative difference of the annual power generation obtained by the scheduling rules is no more than 1%. The effectiveness and practical applicability of the scheduling rules are demonstrated by a case study. This study provides a new perspective for formulating the rules of power generation dispatching.展开更多
This paper studies online scheduling of jobs with kind release times on a single machine. Here "kind release time" means that in online setting, no jobs can be released when the machine is busy. Each job J h...This paper studies online scheduling of jobs with kind release times on a single machine. Here "kind release time" means that in online setting, no jobs can be released when the machine is busy. Each job J has a kind release time r(J) ≥ 0, a processing time p(J) > 0 and a deadline d(J) > 0. The goal is to determine a schedule which maximizes total processing time( p(J)E(J)) or total number( E(J)) of the accepted jobs. For the first objective function p(J)E(J), we first present a lower bound 2(1/2), and then provide an online algorithm LEJ with a competitive ratio of 3. This is the first deterministic algorithm for the problem with a constant competitive ratio. When p(J) ∈ {1, k}, k > 1 is a real number, we first present a lower bound min{(1 + k)/k, 2 k/(1 + k)}, and then we show that LEJ has a competitive ratio of1 + k/k. In particular, when all the k length jobs have tight deadlines, we first present a lower bound max{4/(2 + k), 1}(for p(J)E(J)) and 4/3(for E(J)). Then we prove that LEJ is k/k-competitive for p(J)E(J) and we provide an online algorithm H with a competitive ratio of 2 k/( k + 1) for the second objective function E(J).展开更多
This paper proposes a formal model of the automatic testing system for scheduling strategies in real-time UNIX and describes the algorithm of the key part of the system. The model of the system is an important technol...This paper proposes a formal model of the automatic testing system for scheduling strategies in real-time UNIX and describes the algorithm of the key part of the system. The model of the system is an important technology of the automatization of software development. According to the model presented in the paper, many different kinds of automatic testing systems can be designed and developed easily. At the end of the paper, the prototype proves the feasibility of the model and design.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
This paper considers the parallel machines scheduling problem where jobs are subject to different release times. A constructive heuristic is first proposed to solve the problem in a modest amount of computer time. In ...This paper considers the parallel machines scheduling problem where jobs are subject to different release times. A constructive heuristic is first proposed to solve the problem in a modest amount of computer time. In general, the quality of the solutions provided by heuristics degrades with the increase of the probiem’s scale. Combined the global search ability of genetic algorithm, this paper proposed a hybrid heuristic to improve the quality of solutions further. The computational results show that the hybrid heuristic combines the advantages of heuristic and genetic algorithm effectively and can provide very good solutions to some large problems in a reasonable amount of computer time.展开更多
基金Supported by the National Natural Science Foundation of China (61174040, 61104178)the Fundamental Research Funds for the Central Universities
文摘A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Secondly, an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity. Thirdly, based on the idea of iterated greedy algorithm, some newly designed schemes for employed bee, onlooker bee and scout bee are presented. The performance of the proposed algorithm is tested on the well-known Taillard benchmark set, and the computational results demonstrate the effectiveness of the discrete artificial bee colony algorithm. In addition, the best known solutions of the benchmark set are provided for the blocking flow shop scheduling problem with total flow time criterion.
基金Projects(7107111561273035)supported by the National Natural Science Foundation of China
文摘To solve the scheduling problem of dual-armed cluster tools for wafer fabrications with residency time and reentrant constraints,a heuristic scheduling algorithm was developed.Firstly,on the basis of formulating scheduling problems domain of dual-armed cluster tools,a non-integer programming model was set up with a minimizing objective function of the makespan.Combining characteristics of residency time and reentrant constraints,a scheduling algorithm of searching the optimal operation path of dual-armed transport module was presented under many kinds of robotic scheduling paths for dual-armed cluster tools.Finally,the experiments were designed to evaluate the proposed algorithm.The results show that the proposed algorithm is feasible and efficient for obtaining an optimal scheduling solution of dual-armed cluster tools with residency time and reentrant constraints.
基金the National Natural Science Foundation of China (70631003)the Hefei University of Technology Foundation (071102F).
文摘A class of nonidentical parallel machine scheduling problems are considered in which the goal is to minimize the total weighted completion time. Models and relaxations are collected. Most of these problems are NP-hard, in the strong sense, or open problems, therefore approximation algorithms are studied. The review reveals that there exist some potential areas worthy of further research.
基金supported in part by the National Natural Science Foundation of China (Nos. 61174159, 61101184)
文摘With the development of rapid-response Earth-observing techniques, the demand for reducing a requirements-tasking-effects cycle from 1 day to hours grows rapidly. For instance, a satellite user always wants to receive requested data in near real-time to support their urgent mis- sions, such as dealing with wildfires, volcanoes, flooding events, etc. In this paper, we try to reduce data transmission time for achieving this goal. The new feature of a responsive satellite is that users can receive signals from it directly. Therefore, the traditional satellite control and operational tech- niques need to be improved to accommodate these changes in user needs and technical upgrading. With that in mind, a data transmission topological model is constructed. Based on this model, we can deal with the satellite data transmission problem as a multi-constraint and multi-objective path- scheduling problem. However, there are many optional data transmission paths for each target based on this model, and the shortest path is preferred. In addition, satellites represent scarce resources that must be carefully scheduled in order to satisfy as many consumer requests as possible. To efficiently balance response time and resource utilization, a K-shortest path genetic algorithm is proposed for solving the data transmission problem. Simulations and analysis show the feasibility and the adaptability of the proposed approach.
文摘In present era, one of the most important resources of computer machine is CPU. With the increasing number of application, there exist a large number of processes in the computer system at the same time. Many processes in system simultaneously raise a challenging circumstance of managing the CPU in such a manner that the CPU utilization and processes execution gets optimal performance. The world is still waiting for most efficient algorithm which remains a challenging issue. In this manuscript, we have proposed a new algorithm Progressively Varying Response Ratio Priority a preemptive CPU scheduling algorithm based on the Priority Algorithm and Shortest Remaining Time First. In this scheduling algorithm, the priority is been calculated and the processes with high priority get CPU first or next. For new process, the priority of it becomes equal to inverse of burst time and for the old processes the priority calculation takes place as a ratio of waiting time and remaining burst time. The objective is to get all the processes executed with minimum average waiting time and no starvation. Experiment and comparison show that the VRRP outperforms other CPU scheduling algorithms. It gives better evaluation results in the form of scheduling criteria. We have used the deterministic model to compare the different algorithms.
基金supported by National Natural Science Foundation of CHINA(No.70540024)Re-search Foundation of Ministry of Education of China(No.104107).
文摘Motivated by industrial applications we study a single-machine scheduling problem in which all the jobs are mutu-ally independent and available at time zero.The machine processes the jobs sequentially and it is not idle if there is any job to be pro-cessed.The operation of each job cannot be interrupted.The machine cannot process more than one job at a time.A setup time is needed if the machine switches from one type of job to another.The objective is to find an optimal schedule with the minimal total jobs’completion time.While the sum of jobs’processing time is always a constant,the objective is to minimize the sum of setup times.Ant colony optimization(ACO)is a meta-heuristic that has recently been applied to scheduling problem.In this paper we propose an improved ACO-Branching Ant Colony with Dynamic Perturbation(DPBAC)algorithm for the single-machine schedul-ing problem.DPBAC improves traditional ACO in following aspects:introducing Branching Method to choose starting points;im-proving state transition rules;introducing Mutation Method to shorten tours;improving pheromone updating rules and introduc-ing Conditional Dynamic Perturbation Strategy.Computational results show that DPBAC algorithm is superior to the traditional ACO algorithm.
基金supported by the National Natural Science Foundation of China(NNSFC)(the grant No.60274043)supported by the National High-tech Research&Development Project(863)(the grant No.2002AA412610)
文摘In this paper, by considering the fuzzy nature of the data in real-life problems, single machine scheduling problems with fuzzy processing time and multiple objectives are formulated and an efficient genetic algorithm which is suitable for solving these problems is proposed. As illustrative numerical examples, twenty jobs processing on a machine is considered. The feasibility and effectiveness of the proposed method have been demonstrated in the simulation.
文摘Dynamic exclusive pickup and delivery problem with time windows (DE-PDPTW), aspecial dynamic vehicle scheduling problem, is proposed. Its mathematical description is given andits static properties are analyzed, and then the problem is simplified asthe asymmetrical travelingsalesman problem with time windows. The rolling horizon scheduling algorithm (RHSA) to solve thisdynamic problem is proposed. By the rolling of time horizon, the RHSA can adapt to the problem'sdynamic change and reduce the computation time by dealing with only part of the customers in eachrolling time horizon. Then, its three factors, the current customer window, the scheduling of thecurrent customer window and the rolling strategy, are analyzed. The test results demonstrate theeffectiveness of the RHSA to solve the dynamic vehicle scheduling problem.
文摘Lot scheduling problem with idle time transfer between processes to minimize mean flow time is very important because to minimize mean flow time is to minimize work in process. But the problem is NP hard and no polynomial algorithm exists to guarantee optimal solution. Based the analysis the mathematical structure of the problem, the paper presents a new heuristic algorithm. Computer simulation shows that the proposed heuristic algorithm performs well in terms of both quality of solution and execution speed.
基金supported by the National Natural Science Foundation of China(61671462).
文摘It is of great significance to carry out effective scheduling for the carrier-based aircraft flight deck operations.In this paper,the precedence constraints and resource constraints in flight deck operations are analyzed,then the model of the multi-aircraft integrated scheduling problem with transfer times(MAISPTT)is established.A dual population multi-operator genetic algorithm(DPMOGA)is proposed for solving the problem.In the algorithm,the dual population structure and random-key encoding modified by starting/ending time of operations are adopted,and multiple genetic operators are self-adaptively used to obtain better encodings.In order to conduct the mapping from encodings to feasible schedules,serial and parallel scheduling generation scheme-based decoding operators,each of which adopts different justified mechanisms in two separated populations,are introduced.The superiority of the DPMOGA is verified by simulation experiments.
基金This project is supported by Key Science-Technology Project of Shanghai City Tenth Five-Year-Plan, China (No.031111002)Specialized Research Fund for the Doctoral Program of Higher Education, China (No.20040247033)Municipal Key Basic Research Program of Shanghai, China (No.05JC14060)
文摘In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.
基金the Science and Technology Cooperation Research and Development Project of Sichuan Provincial Academy and University(Grant No.2019YFSY0024)the Key Research and Development Program in Sichuan Province of China(Grant No.2019YFG0050)the Natural Science Foundation of Guangxi Province of China(Grant No.AD19245021).
文摘Support vehicles are part of the main body of airport ground operations,and their scheduling efficiency directly impacts flight delays.A mathematical model is constructed and the responsiveness of support vehicles for current operational demands is proposed to study optimization algorithms for vehicle scheduling.The model is based on the constraint relationship of the initial operation time,time window,and gate position distribution,which gives an improvement to the ant colony algorithm(ACO).The impacts of the improved ACO as used for support vehicle optimization are compared and analyzed.The results show that the scheduling scheme of refueling trucks based on the improved ACO can reduce flight delays caused by refueling operations by 56.87%,indicating the improved ACO can improve support vehicle scheduling.Besides,the improved ACO can jump out of local optima,which can balance the working time of refueling trucks.This research optimizes the scheduling scheme of support vehicles under the existing conditions of airports,which has practical significance to fully utilize ground service resources,improve the efficiency of airport ground operations,and effectively reduce flight delays caused by ground service support.
基金Supported by the National Natural Science Founda-tion of China (60373088)
文摘We put forward an optimal disk schedule with n disk requests and prove its optimality mathematically.Generalizing the idea of an optimal disk schedule, we remove the limit of n requests and, at the same time, consider the dynamically arrival model of disk requests to obtain an algorithm, shortest path first-fit first （SPFF）. This algorithm is based on the shortest path of disk head motion constructed by all the pendent requests. From view of the head moving distance, it has the stronger glohality than SSTF. From view of the head-moving direction, it has the better flexibility than SCAN. Therefore, SPFF keeps the advantage of SCAN and, at the same time, absorbs the strength of SSTF. The algorithm SPFF not only shows the more superiority than other scheduling polices, but also have higher adjustability to meet the computer system＇s different demands.
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.
基金supported by the National Key Basic Research Development Program of China (Grant No. 2002CCA00700)
文摘Power generation dispatching is a large complex system problem with multi-dimensional and nonlinear characteristics. A mathematical model was established based on the principle of reservoir operation. A large quantity of optimal scheduling processes were obtained by calculating the daily runoff process within three typical years, and a large number of simulated daily runoff processes were obtained using the progressive optimality algorithm （POA） in combination with the genetic algorithm （GA）. After analyzing the optimal scheduling processes, the corresponding scheduling rules were determined, and the practical formulas were obtained. These rules can make full use of the rolling runoff forecast and carry out the rolling scheduling. Compared with the optimized results, the maximum relative difference of the annual power generation obtained by the scheduling rules is no more than 1%. The effectiveness and practical applicability of the scheduling rules are demonstrated by a case study. This study provides a new perspective for formulating the rules of power generation dispatching.
基金Supported by the National Natural Science Foundation of China(11501279,11501171,11671188,and11401604)the Young Backbone Teachers of Luoyang Normal University(2018XJGGJS-10)Henan Colleges(2015GGJS-193)
文摘This paper studies online scheduling of jobs with kind release times on a single machine. Here "kind release time" means that in online setting, no jobs can be released when the machine is busy. Each job J has a kind release time r(J) ≥ 0, a processing time p(J) > 0 and a deadline d(J) > 0. The goal is to determine a schedule which maximizes total processing time( p(J)E(J)) or total number( E(J)) of the accepted jobs. For the first objective function p(J)E(J), we first present a lower bound 2(1/2), and then provide an online algorithm LEJ with a competitive ratio of 3. This is the first deterministic algorithm for the problem with a constant competitive ratio. When p(J) ∈ {1, k}, k > 1 is a real number, we first present a lower bound min{(1 + k)/k, 2 k/(1 + k)}, and then we show that LEJ has a competitive ratio of1 + k/k. In particular, when all the k length jobs have tight deadlines, we first present a lower bound max{4/(2 + k), 1}(for p(J)E(J)) and 4/3(for E(J)). Then we prove that LEJ is k/k-competitive for p(J)E(J) and we provide an online algorithm H with a competitive ratio of 2 k/( k + 1) for the second objective function E(J).
基金the Defense Advanced research Projects Agency of the Department of Defense (No.15.3.2).
文摘This paper proposes a formal model of the automatic testing system for scheduling strategies in real-time UNIX and describes the algorithm of the key part of the system. The model of the system is an important technology of the automatization of software development. According to the model presented in the paper, many different kinds of automatic testing systems can be designed and developed easily. At the end of the paper, the prototype proves the feasibility of the model and design.
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.
文摘This paper considers the parallel machines scheduling problem where jobs are subject to different release times. A constructive heuristic is first proposed to solve the problem in a modest amount of computer time. In general, the quality of the solutions provided by heuristics degrades with the increase of the probiem’s scale. Combined the global search ability of genetic algorithm, this paper proposed a hybrid heuristic to improve the quality of solutions further. The computational results show that the hybrid heuristic combines the advantages of heuristic and genetic algorithm effectively and can provide very good solutions to some large problems in a reasonable amount of computer time.
