Bottleneck stage and reentrance often exist in real-life manufacturing processes;however,the previous research rarely addresses these two processing conditions in a scheduling problem.In this study,a reentrant hybrid ...Bottleneck stage and reentrance often exist in real-life manufacturing processes;however,the previous research rarely addresses these two processing conditions in a scheduling problem.In this study,a reentrant hybrid flow shop scheduling problem(RHFSP)with a bottleneck stage is considered,and an elite-class teaching-learning-based optimization(ETLBO)algorithm is proposed to minimize maximum completion time.To produce high-quality solutions,teachers are divided into formal ones and substitute ones,and multiple classes are formed.The teacher phase is composed of teacher competition and teacher teaching.The learner phase is replaced with a reinforcement search of the elite class.Adaptive adjustment on teachers and classes is established based on class quality,which is determined by the number of elite solutions in class.Numerous experimental results demonstrate the effectiveness of new strategies,and ETLBO has a significant advantage in solving the considered RHFSP.展开更多
This paper considers a scheduling problem in two-stage hybrid flow shop,where the first stage consists of two machines formed an open shop and the other stage has only one machine.The objective is to minimize the make...This paper considers a scheduling problem in two-stage hybrid flow shop,where the first stage consists of two machines formed an open shop and the other stage has only one machine.The objective is to minimize the makespan,i.e.,the maximum completion time of all jobs.We first show the problem is NP-hard in the strong sense,then we present two heuristics to solve the problem.Computational experiments show that the combined algorithm of the two heuristics performs well on randomly generated problem instances.展开更多
This paper considers a hybrid two-stage flow-shop scheduling problem with m identical parallel machines on one stage and a batch processor on the other stage. The processing time of job Jj on any of m identical parall...This paper considers a hybrid two-stage flow-shop scheduling problem with m identical parallel machines on one stage and a batch processor on the other stage. The processing time of job Jj on any of m identical parallel machines is aj≡ a (j∈N), and the processing time of job Jj is bj(j∈N) on a batch processor M. We take makespan (Cmax) as our minimization objective. In this paper, for the problem of FSMP-BI (m identical parallel machines on the first stage and a batch processor on the second stage), based on the algorithm given by Sung and Choung for the problem of 1| rj, BI | Cmax under the constraint of the given processing sequence, we develop an optimal dynamic programming Algorithm H1 for it in max{O(nlogn), O(nB)} time. A max{O(nlogn), O(nB)} time symmetric Algorithm H2 is given then for the problem of BI-FSMP (a batch processor on the first stage and m identical parallel machines on the second stage).展开更多
To solve the distributed hybrid flow shop scheduling problem(DHFS)in raw glass manufacturing systems,we investigated an improved hyperplane assisted evolutionary algorithm(IhpaEA).Two objectives are simultaneously con...To solve the distributed hybrid flow shop scheduling problem(DHFS)in raw glass manufacturing systems,we investigated an improved hyperplane assisted evolutionary algorithm(IhpaEA).Two objectives are simultaneously considered,namely,the maximum completion time and the total energy consumptions.Firstly,each solution is encoded by a three-dimensional vector,i.e.,factory assignment,scheduling,and machine assignment.Subsequently,an efficient initialization strategy embeds two heuristics are developed,which can increase the diversity of the population.Then,to improve the global search abilities,a Pareto-based crossover operator is designed to take more advantage of non-dominated solutions.Furthermore,a local search heuristic based on three parts encoding is embedded to enhance the searching performance.To enhance the local search abilities,the cooperation of the search operator is designed to obtain better non-dominated solutions.Finally,the experimental results demonstrate that the proposed algorithm is more efficient than the other three state-of-the-art algorithms.The results show that the Pareto optimal solution set obtained by the improved algorithm is superior to that of the traditional multiobjective algorithm in terms of diversity and convergence of the solution.展开更多
This work aims to resolve the distributed heterogeneous permutation flow shop scheduling problem(DHPFSP)with minimizing makespan and total energy consumption(TEC).To solve this NP-hard problem,this work proposed a com...This work aims to resolve the distributed heterogeneous permutation flow shop scheduling problem(DHPFSP)with minimizing makespan and total energy consumption(TEC).To solve this NP-hard problem,this work proposed a competitive and cooperative-based strength Pareto evolutionary algorithm(CCSPEA)which contains the following features:1)An initialization based on three heuristic rules is developed to generate a population with great diversity and convergence.2)A comprehensive metric combining convergence and diversity metrics is used to better represent the heuristic information of a solution.3)A competitive selection is designed which divides the population into a winner and a loser swarms based on the comprehensive metric.4)A cooperative evolutionary schema is proposed for winner and loser swarms to accelerate the convergence of global search.5)Five local search strategies based on problem knowledge are designed to improve convergence.6)Aproblem-based energy-saving strategy is presented to reduce TEC.Finally,to evaluate the performance of CCSPEA,it is compared to four state-of-art and run on 22 instances based on the Taillard benchmark.The numerical experiment results demonstrate that 1)the proposed comprehensive metric can efficiently represent the heuristic information of each solution to help the later step divide the population.2)The global search based on the competitive and cooperative schema can accelerate loser solutions convergence and further improve the winner’s exploration.3)The problembased initialization,local search,and energy-saving strategies can efficiently reduce the makespan and TEC.4)The proposed CCSPEA is superior to the state-of-art for solving DHPFSP.展开更多
The process flow and the main devices of a new two-stage dry-fed coal gasification pilot plant with a throughout of 36 t/d are introduced in this paper. For comparison with the traditional one-stage gasifiers, the inf...The process flow and the main devices of a new two-stage dry-fed coal gasification pilot plant with a throughout of 36 t/d are introduced in this paper. For comparison with the traditional one-stage gasifiers, the influences of the coal feed ratio between two stages on the performance of the gasifier are detailedly studied by a series of experiments. The results reveal that the two-stage gasification decreases the temperature of the syngas at the outlet of the gasifier, simplifies the gasification process, and reduces the size of the syngas cooler. Moreover, the cold gas efficiency of the gasifier can be improved by using the two-stage gasification. In our experiments, the efficiency is about 3%-6% higher than the existing one-stage gasifiers.展开更多
The traditional practice of employing a two-stage coal-fed gasification process is to feed all of the oxygen to provide a vigorous amount of combustion in the first stage but only feed the coal without oxygen in the s...The traditional practice of employing a two-stage coal-fed gasification process is to feed all of the oxygen to provide a vigorous amount of combustion in the first stage but only feed the coal without oxygen in the second stage to allow the endothermic gasification process to occur downstream of the second stage. One of the merits of this 2-stage practice is to keep the gasifier temperature low downstream from the 2nd stage. This helps to extend the life of refractory bricks, decrease gasifier shut-down frequency for scheduled maintenance, and reduce the maintenance costs. In this traditional 2-stage practice, the temperature reduction in the second stage is achieved at the expense of a higher than normal temperature in the first stage. This study investigates a concept totally opposite to the traditional two-stage coal feeding practices in which the injected oxygen is split between the two stages, while all the coal is fed into the first stage. The hypothesis of this two-stage oxygen injection is that a distributed oxygen injection scheme can also distribute the release of heat to a larger gasifier volume and, thus, reduce the peak temperature distribution in the gasifier. The increased life expectancy and reduced maintenance of the refractory bricks can prevail in the entire gasifier and not just downstream from the second stage. In this study, both experiments and computational simulations have been performed to verify the hypothesis. A series of experiments conducted at 2.5 - 3.0 bars shows that the peak temperature and temperature range in the gasifier do decrease from 600?C - 1550?C with one stage oxygen injection to 950?C - 1230?C with a 60 - 40 oxygen split-injection. The CFD results conducted at 2.5 bars show that 1) the carbon conversion ratio for different oxygen injection schemes are all above 95%;2) H2 (about 70% vol.) dominates the syngas composition at the exit;3) the 80% - 20% case yields the lowest peak temperature and the most uniform temperature distribution along the gasifier;and 4) the 40% - 60% case produces the syngas with the highest HHV. Both experimental data and CFD predictions verify the hypothesis that it is feasible to reduce the peak temperature and achieve more uniform temperature in the gasifier by adequately controlling a two-stage oxygen injection with only minor changes of the composition and heating value of the syngas.展开更多
基金the National Natural Science Foundation of China(Grant Number 61573264).
文摘Bottleneck stage and reentrance often exist in real-life manufacturing processes;however,the previous research rarely addresses these two processing conditions in a scheduling problem.In this study,a reentrant hybrid flow shop scheduling problem(RHFSP)with a bottleneck stage is considered,and an elite-class teaching-learning-based optimization(ETLBO)algorithm is proposed to minimize maximum completion time.To produce high-quality solutions,teachers are divided into formal ones and substitute ones,and multiple classes are formed.The teacher phase is composed of teacher competition and teacher teaching.The learner phase is replaced with a reinforcement search of the elite class.Adaptive adjustment on teachers and classes is established based on class quality,which is determined by the number of elite solutions in class.Numerous experimental results demonstrate the effectiveness of new strategies,and ETLBO has a significant advantage in solving the considered RHFSP.
基金Supported by the National Natural Science Foundation of China(11071220,11001242,11201428)Zhejiang Provincial Natural Science Foundation of China(LY13A010015)Educational Commission of Zhejiang Province of China(Y201019076)
文摘This paper considers a scheduling problem in two-stage hybrid flow shop,where the first stage consists of two machines formed an open shop and the other stage has only one machine.The objective is to minimize the makespan,i.e.,the maximum completion time of all jobs.We first show the problem is NP-hard in the strong sense,then we present two heuristics to solve the problem.Computational experiments show that the combined algorithm of the two heuristics performs well on randomly generated problem instances.
基金Sponsored by the Innovation Foundation of Shanghai University(Grant No.A.10-0101-07 -406)NNSF of China(Grant No.60874039)
文摘This paper considers a hybrid two-stage flow-shop scheduling problem with m identical parallel machines on one stage and a batch processor on the other stage. The processing time of job Jj on any of m identical parallel machines is aj≡ a (j∈N), and the processing time of job Jj is bj(j∈N) on a batch processor M. We take makespan (Cmax) as our minimization objective. In this paper, for the problem of FSMP-BI (m identical parallel machines on the first stage and a batch processor on the second stage), based on the algorithm given by Sung and Choung for the problem of 1| rj, BI | Cmax under the constraint of the given processing sequence, we develop an optimal dynamic programming Algorithm H1 for it in max{O(nlogn), O(nB)} time. A max{O(nlogn), O(nB)} time symmetric Algorithm H2 is given then for the problem of BI-FSMP (a batch processor on the first stage and m identical parallel machines on the second stage).
文摘To solve the distributed hybrid flow shop scheduling problem(DHFS)in raw glass manufacturing systems,we investigated an improved hyperplane assisted evolutionary algorithm(IhpaEA).Two objectives are simultaneously considered,namely,the maximum completion time and the total energy consumptions.Firstly,each solution is encoded by a three-dimensional vector,i.e.,factory assignment,scheduling,and machine assignment.Subsequently,an efficient initialization strategy embeds two heuristics are developed,which can increase the diversity of the population.Then,to improve the global search abilities,a Pareto-based crossover operator is designed to take more advantage of non-dominated solutions.Furthermore,a local search heuristic based on three parts encoding is embedded to enhance the searching performance.To enhance the local search abilities,the cooperation of the search operator is designed to obtain better non-dominated solutions.Finally,the experimental results demonstrate that the proposed algorithm is more efficient than the other three state-of-the-art algorithms.The results show that the Pareto optimal solution set obtained by the improved algorithm is superior to that of the traditional multiobjective algorithm in terms of diversity and convergence of the solution.
基金supported by the National Natural Science Foundation of China under Grant Nos.62076225 and 62122093the Open Project of Xiangjiang Laboratory under Grant No 22XJ02003.
文摘This work aims to resolve the distributed heterogeneous permutation flow shop scheduling problem(DHPFSP)with minimizing makespan and total energy consumption(TEC).To solve this NP-hard problem,this work proposed a competitive and cooperative-based strength Pareto evolutionary algorithm(CCSPEA)which contains the following features:1)An initialization based on three heuristic rules is developed to generate a population with great diversity and convergence.2)A comprehensive metric combining convergence and diversity metrics is used to better represent the heuristic information of a solution.3)A competitive selection is designed which divides the population into a winner and a loser swarms based on the comprehensive metric.4)A cooperative evolutionary schema is proposed for winner and loser swarms to accelerate the convergence of global search.5)Five local search strategies based on problem knowledge are designed to improve convergence.6)Aproblem-based energy-saving strategy is presented to reduce TEC.Finally,to evaluate the performance of CCSPEA,it is compared to four state-of-art and run on 22 instances based on the Taillard benchmark.The numerical experiment results demonstrate that 1)the proposed comprehensive metric can efficiently represent the heuristic information of each solution to help the later step divide the population.2)The global search based on the competitive and cooperative schema can accelerate loser solutions convergence and further improve the winner’s exploration.3)The problembased initialization,local search,and energy-saving strategies can efficiently reduce the makespan and TEC.4)The proposed CCSPEA is superior to the state-of-art for solving DHPFSP.
基金This work was supported by the National High-Tech Research and Development Plan of China (No2003AA522030)
文摘The process flow and the main devices of a new two-stage dry-fed coal gasification pilot plant with a throughout of 36 t/d are introduced in this paper. For comparison with the traditional one-stage gasifiers, the influences of the coal feed ratio between two stages on the performance of the gasifier are detailedly studied by a series of experiments. The results reveal that the two-stage gasification decreases the temperature of the syngas at the outlet of the gasifier, simplifies the gasification process, and reduces the size of the syngas cooler. Moreover, the cold gas efficiency of the gasifier can be improved by using the two-stage gasification. In our experiments, the efficiency is about 3%-6% higher than the existing one-stage gasifiers.
文摘The traditional practice of employing a two-stage coal-fed gasification process is to feed all of the oxygen to provide a vigorous amount of combustion in the first stage but only feed the coal without oxygen in the second stage to allow the endothermic gasification process to occur downstream of the second stage. One of the merits of this 2-stage practice is to keep the gasifier temperature low downstream from the 2nd stage. This helps to extend the life of refractory bricks, decrease gasifier shut-down frequency for scheduled maintenance, and reduce the maintenance costs. In this traditional 2-stage practice, the temperature reduction in the second stage is achieved at the expense of a higher than normal temperature in the first stage. This study investigates a concept totally opposite to the traditional two-stage coal feeding practices in which the injected oxygen is split between the two stages, while all the coal is fed into the first stage. The hypothesis of this two-stage oxygen injection is that a distributed oxygen injection scheme can also distribute the release of heat to a larger gasifier volume and, thus, reduce the peak temperature distribution in the gasifier. The increased life expectancy and reduced maintenance of the refractory bricks can prevail in the entire gasifier and not just downstream from the second stage. In this study, both experiments and computational simulations have been performed to verify the hypothesis. A series of experiments conducted at 2.5 - 3.0 bars shows that the peak temperature and temperature range in the gasifier do decrease from 600?C - 1550?C with one stage oxygen injection to 950?C - 1230?C with a 60 - 40 oxygen split-injection. The CFD results conducted at 2.5 bars show that 1) the carbon conversion ratio for different oxygen injection schemes are all above 95%;2) H2 (about 70% vol.) dominates the syngas composition at the exit;3) the 80% - 20% case yields the lowest peak temperature and the most uniform temperature distribution along the gasifier;and 4) the 40% - 60% case produces the syngas with the highest HHV. Both experimental data and CFD predictions verify the hypothesis that it is feasible to reduce the peak temperature and achieve more uniform temperature in the gasifier by adequately controlling a two-stage oxygen injection with only minor changes of the composition and heating value of the syngas.
