Inspired by cooperative hunting of lionesses,this paper presents a Lions Group Algorithm for cooperative hunting tasks involving multiple AUVs(autonomous underwater vehicles).The lions group algorithm is developed aro...Inspired by cooperative hunting of lionesses,this paper presents a Lions Group Algorithm for cooperative hunting tasks involving multiple AUVs(autonomous underwater vehicles).The lions group algorithm is developed around two core relationships:the dynamic game relationship between the hunters and the target and the cooperative relationship between hunters.In this paper,the lions group algorithm is divided into three stages.In each stage,the dynamic game model between the hunters and the target is constructed,and the cooperation model between the hunters is constructed.At the same time,in these three phases,a dynamic allocationmechanism for the roles and tasks of hunterswas established.The simulation experiment revealed the hunting effect.The results show that the path planning and obstacle avoidance strategy of the hunters,the target’s escape strategy,the complexity of the environment,and the speed relationship between the hunter and the target affect the hunting effect.展开更多
AIM： To figure out the contributed factors of the hospitalization expenses of senile cataract patients（HECP） and build up an area-specified senile cataract diagnosis related group（DRG） of Shanghai thereby formula...AIM： To figure out the contributed factors of the hospitalization expenses of senile cataract patients（HECP） and build up an area-specified senile cataract diagnosis related group（DRG） of Shanghai thereby formulating the reference range of HECP and providing scientific basis for the fair use and supervision of the health care insurance fund.METHODS： The data was collected from the first page of the medical records of 22 097 hospitalized patients from tertiary hospitals in Shanghai from 2010 to 2012 whose major diagnosis were senile cataract. Firstly, we analyzed the influence factors of HECP using univariate and multivariate analysis. DRG grouping was conducted according to the exhaustive Chi-squared automatic interaction detector（E-CHAID） model, using HECP as target variable. Finally we evaluated the grouping results using non-parametric test such as Kruskal-Wallis H test, RIV, CV, etc.RESULTS： The 6 DRGs were established as well as criterion of HECP, using age, sex, type of surgery and whether complications/comorbidities occurred as the key variables of classification node of senile cataract cases.CONCLUSION： The grouping of senile cataract cases based on E-CHAID algorithm is reasonable. And the criterion of HECP based on DRG can provide a feasible way of management in the fair use and supervision of medical insurance fund.展开更多
The artificial immune system,an excellent prototype for developingMachine Learning,is inspired by the function of the powerful natural immune system.As one of the prevalent classifiers,the Dendritic Cell Algorithm(DCA...The artificial immune system,an excellent prototype for developingMachine Learning,is inspired by the function of the powerful natural immune system.As one of the prevalent classifiers,the Dendritic Cell Algorithm(DCA)has been widely used to solve binary problems in the real world.The classification of DCA depends on a data preprocessing procedure to generate input signals,where feature selection and signal categorization are themain work.However,the results of these studies also show that the signal generation of DCA is relatively weak,and all of them utilized a filter strategy to remove unimportant attributes.Ignoring filtered features and applying expertise may not produce an optimal classification result.To overcome these limitations,this study models feature selection and signal categorization into feature grouping problems.This study hybridizes Grouping Genetic Algorithm(GGA)with DCA to propose a novel DCA version,GGA-DCA,for accomplishing feature selection and signal categorization in a search process.The GGA-DCA aims to search for the optimal feature grouping scheme without expertise automatically.In this study,the data coding and operators of GGA are redefined for grouping tasks.The experimental results show that the proposed algorithm has significant advantages over the compared DCA expansion algorithms in terms of signal generation.展开更多
This paper presents the two-machine flowshop group scheduling problem with the optimal objective of maximum lateness. A dominance rule within group and a dominance rule between groups are established. These dominance ...This paper presents the two-machine flowshop group scheduling problem with the optimal objective of maximum lateness. A dominance rule within group and a dominance rule between groups are established. These dominance rules along with a previously established dominance rule are used to develop a heuristic algorithm. Experimental results are given and analyzed.展开更多
To overcome the default of single search tendency, the ants in the colony are divided into several sub-groups. The ants in different subgroups have different trail information and expectation coefficients. The simulat...To overcome the default of single search tendency, the ants in the colony are divided into several sub-groups. The ants in different subgroups have different trail information and expectation coefficients. The simulated annealing method is introduced to the algorithm. Through setting the temperature changing with the iterations, after each turn of tours, the solution set obtained by the ants is taken as the candidate set. The update set is obtained by adding the solutions in the candidate set to the previous update set with the probability determined by the temperature. The solutions in the candidate set are used to update the trail information. In each turn of updating, the current best solution is also used to enhance the trail information on the current best route. The trail information is reset when the algorithm is in stagnation state. The computer experiments demonstrate that the proposed algorithm has higher stability and convergence speed.展开更多
A simplified group search optimizer algorithm denoted as"SGSO"for large scale global optimization is presented in this paper to obtain a simple algorithm with superior performance on high-dimensional problem...A simplified group search optimizer algorithm denoted as"SGSO"for large scale global optimization is presented in this paper to obtain a simple algorithm with superior performance on high-dimensional problems.The SGSO adopts an improved sharing strategy which shares information of not only the best member but also the other good members,and uses a simpler search method instead of searching by the head angle.Furthermore,the SGSO increases the percentage of scroungers to accelerate convergence speed.Compared with genetic algorithm(GA),particle swarm optimizer(PSO)and group search optimizer(GSO),SGSO is tested on seven benchmark functions with dimensions 30,100,500 and 1 000.It can be concluded that the SGSO has a remarkably superior performance to GA,PSO and GSO for large scale global optimization.展开更多
Aiming at the flexible flowshop group scheduling problem,taking sequence dependent setup time and machine skipping into account, a mathematical model for minimizing makespan is established,and a hybrid differential ev...Aiming at the flexible flowshop group scheduling problem,taking sequence dependent setup time and machine skipping into account, a mathematical model for minimizing makespan is established,and a hybrid differential evolution( HDE) algorithm based on greedy constructive procedure( GCP) is proposed,which combines differential evolution( DE) with tabu search( TS). DE is applied to generating the elite individuals of population,while TS is used for finding the optimal value by making perturbation in selected elite individuals. A lower bounding technique is developed to evaluate the quality of proposed algorithm. Experimental results verify the effectiveness and feasibility of proposed algorithm.展开更多
In this article, we have described the Todd-Coxeter algorithm. Indeed, the Todd-Coxeter algorithm is a mathematical tool used in the field of group theory. It makes it possible to determine different possible presenta...In this article, we have described the Todd-Coxeter algorithm. Indeed, the Todd-Coxeter algorithm is a mathematical tool used in the field of group theory. It makes it possible to determine different possible presentations of a group, i.e. different ways of expressing its elements and operations. We have also applied this algorithm to a subgroup generated H by G;where we obtained a table of the subgroup, three tables of relators including: Table of the relator aaaa;Table of the relator abab;Table of the relator bbb and a multiplication table aa'bb'. Once the algorithm is complete, the unit of H in G is 6. We have explicitly obtained a homomorphism of G in the group of permutations of H/G which is isomorphic to G6;where we have noticed that it is injective: in fact, an element of the nucleus belongs to the intersection of the xHx−1for x∈G, in particular, it belongs to H;on the other hand, the image of H in G6 is of order 4, so the nucleus is reduced to the neutral element.展开更多
It is significant to combine multiple tasks into an optimal work package in decision-making of aircraft maintenance to reduce cost,so a cost rate model of combinatorial maintenance is an urgent need.However,the optima...It is significant to combine multiple tasks into an optimal work package in decision-making of aircraft maintenance to reduce cost,so a cost rate model of combinatorial maintenance is an urgent need.However,the optimal combination under various constraints not only involves numerical calculations but also is an NP-hard combinatorial problem.To solve the problem,an adaptive genetic algorithm based on cluster search,which is divided into two phases,is put forward.In the first phase,according to the density,all individuals can be homogeneously scattered over the whole solution space through crossover and mutation and better individuals are collected as candidate cluster centres.In the second phase,the search is confined to the neighbourhood of some selected possible solutions to accurately solve with cluster radius decreasing slowly,meanwhile all clusters continuously move to better regions until all the peaks in the question space is searched.This algorithm can efficiently solve the combination problem.Taking the optimization on decision-making of aircraft maintenance by the algorithm for an example,maintenance which combines multiple parts or tasks can significantly enhance economic benefit when the halt cost is rather high.展开更多
This paper considers single-machine scheduling problems in group technology with the jobs' processing times being simple linear functions of their start times.The objective functions are the ~minimizing of makespa...This paper considers single-machine scheduling problems in group technology with the jobs' processing times being simple linear functions of their start times.The objective functions are the ~minimizing of makespan and total weighted completion time.Some optimal conditions and algorithms are given and the fact that the problem of total weighted completion times is NP-hard is proved.展开更多
文摘Inspired by cooperative hunting of lionesses,this paper presents a Lions Group Algorithm for cooperative hunting tasks involving multiple AUVs(autonomous underwater vehicles).The lions group algorithm is developed around two core relationships:the dynamic game relationship between the hunters and the target and the cooperative relationship between hunters.In this paper,the lions group algorithm is divided into three stages.In each stage,the dynamic game model between the hunters and the target is constructed,and the cooperation model between the hunters is constructed.At the same time,in these three phases,a dynamic allocationmechanism for the roles and tasks of hunterswas established.The simulation experiment revealed the hunting effect.The results show that the path planning and obstacle avoidance strategy of the hunters,the target’s escape strategy,the complexity of the environment,and the speed relationship between the hunter and the target affect the hunting effect.
基金Supported by the Key Research and Development Program of Hunan Province(No.2017SK2011)
文摘AIM： To figure out the contributed factors of the hospitalization expenses of senile cataract patients（HECP） and build up an area-specified senile cataract diagnosis related group（DRG） of Shanghai thereby formulating the reference range of HECP and providing scientific basis for the fair use and supervision of the health care insurance fund.METHODS： The data was collected from the first page of the medical records of 22 097 hospitalized patients from tertiary hospitals in Shanghai from 2010 to 2012 whose major diagnosis were senile cataract. Firstly, we analyzed the influence factors of HECP using univariate and multivariate analysis. DRG grouping was conducted according to the exhaustive Chi-squared automatic interaction detector（E-CHAID） model, using HECP as target variable. Finally we evaluated the grouping results using non-parametric test such as Kruskal-Wallis H test, RIV, CV, etc.RESULTS： The 6 DRGs were established as well as criterion of HECP, using age, sex, type of surgery and whether complications/comorbidities occurred as the key variables of classification node of senile cataract cases.CONCLUSION： The grouping of senile cataract cases based on E-CHAID algorithm is reasonable. And the criterion of HECP based on DRG can provide a feasible way of management in the fair use and supervision of medical insurance fund.
基金NSFC http://www.nsfc.gov.cn/for the support through Grants No.61877045Fundamental Research Project of Shenzhen Science and Technology Program for the support through Grants No.JCYJ2016042815-3956266.
文摘The artificial immune system,an excellent prototype for developingMachine Learning,is inspired by the function of the powerful natural immune system.As one of the prevalent classifiers,the Dendritic Cell Algorithm(DCA)has been widely used to solve binary problems in the real world.The classification of DCA depends on a data preprocessing procedure to generate input signals,where feature selection and signal categorization are themain work.However,the results of these studies also show that the signal generation of DCA is relatively weak,and all of them utilized a filter strategy to remove unimportant attributes.Ignoring filtered features and applying expertise may not produce an optimal classification result.To overcome these limitations,this study models feature selection and signal categorization into feature grouping problems.This study hybridizes Grouping Genetic Algorithm(GGA)with DCA to propose a novel DCA version,GGA-DCA,for accomplishing feature selection and signal categorization in a search process.The GGA-DCA aims to search for the optimal feature grouping scheme without expertise automatically.In this study,the data coding and operators of GGA are redefined for grouping tasks.The experimental results show that the proposed algorithm has significant advantages over the compared DCA expansion algorithms in terms of signal generation.
文摘This paper presents the two-machine flowshop group scheduling problem with the optimal objective of maximum lateness. A dominance rule within group and a dominance rule between groups are established. These dominance rules along with a previously established dominance rule are used to develop a heuristic algorithm. Experimental results are given and analyzed.
基金Project supported by the National Natural Science Foundation of China (Grant No.50608069)
文摘To overcome the default of single search tendency, the ants in the colony are divided into several sub-groups. The ants in different subgroups have different trail information and expectation coefficients. The simulated annealing method is introduced to the algorithm. Through setting the temperature changing with the iterations, after each turn of tours, the solution set obtained by the ants is taken as the candidate set. The update set is obtained by adding the solutions in the candidate set to the previous update set with the probability determined by the temperature. The solutions in the candidate set are used to update the trail information. In each turn of updating, the current best solution is also used to enhance the trail information on the current best route. The trail information is reset when the algorithm is in stagnation state. The computer experiments demonstrate that the proposed algorithm has higher stability and convergence speed.
基金the Science and Technology Planning Project of Hunan Province(No.2011TP4016-3)the Construct Program of the Key Discipline(Technology of Computer Application)in Xiangnan University
文摘A simplified group search optimizer algorithm denoted as"SGSO"for large scale global optimization is presented in this paper to obtain a simple algorithm with superior performance on high-dimensional problems.The SGSO adopts an improved sharing strategy which shares information of not only the best member but also the other good members,and uses a simpler search method instead of searching by the head angle.Furthermore,the SGSO increases the percentage of scroungers to accelerate convergence speed.Compared with genetic algorithm(GA),particle swarm optimizer(PSO)and group search optimizer(GSO),SGSO is tested on seven benchmark functions with dimensions 30,100,500 and 1 000.It can be concluded that the SGSO has a remarkably superior performance to GA,PSO and GSO for large scale global optimization.
基金Shanghai Municipal Natural Science Foundation of China(No.10ZR1431700)
文摘Aiming at the flexible flowshop group scheduling problem,taking sequence dependent setup time and machine skipping into account, a mathematical model for minimizing makespan is established,and a hybrid differential evolution( HDE) algorithm based on greedy constructive procedure( GCP) is proposed,which combines differential evolution( DE) with tabu search( TS). DE is applied to generating the elite individuals of population,while TS is used for finding the optimal value by making perturbation in selected elite individuals. A lower bounding technique is developed to evaluate the quality of proposed algorithm. Experimental results verify the effectiveness and feasibility of proposed algorithm.
文摘In this article, we have described the Todd-Coxeter algorithm. Indeed, the Todd-Coxeter algorithm is a mathematical tool used in the field of group theory. It makes it possible to determine different possible presentations of a group, i.e. different ways of expressing its elements and operations. We have also applied this algorithm to a subgroup generated H by G;where we obtained a table of the subgroup, three tables of relators including: Table of the relator aaaa;Table of the relator abab;Table of the relator bbb and a multiplication table aa'bb'. Once the algorithm is complete, the unit of H in G is 6. We have explicitly obtained a homomorphism of G in the group of permutations of H/G which is isomorphic to G6;where we have noticed that it is injective: in fact, an element of the nucleus belongs to the intersection of the xHx−1for x∈G, in particular, it belongs to H;on the other hand, the image of H in G6 is of order 4, so the nucleus is reduced to the neutral element.
基金supported by the National Natural Science Foundation of China(6107901361079014+4 种基金61403198)the National Natural Science Funds and Civil Aviaiton Mutual Funds(U1533128U1233114)the Programs of Natural Science Foundation of China and China Civil Aviation Joint Fund(60939003)the Natural Science Foundation of Jiangsu Province in China(BK2011737)
文摘It is significant to combine multiple tasks into an optimal work package in decision-making of aircraft maintenance to reduce cost,so a cost rate model of combinatorial maintenance is an urgent need.However,the optimal combination under various constraints not only involves numerical calculations but also is an NP-hard combinatorial problem.To solve the problem,an adaptive genetic algorithm based on cluster search,which is divided into two phases,is put forward.In the first phase,according to the density,all individuals can be homogeneously scattered over the whole solution space through crossover and mutation and better individuals are collected as candidate cluster centres.In the second phase,the search is confined to the neighbourhood of some selected possible solutions to accurately solve with cluster radius decreasing slowly,meanwhile all clusters continuously move to better regions until all the peaks in the question space is searched.This algorithm can efficiently solve the combination problem.Taking the optimization on decision-making of aircraft maintenance by the algorithm for an example,maintenance which combines multiple parts or tasks can significantly enhance economic benefit when the halt cost is rather high.
文摘This paper considers single-machine scheduling problems in group technology with the jobs' processing times being simple linear functions of their start times.The objective functions are the ~minimizing of makespan and total weighted completion time.Some optimal conditions and algorithms are given and the fact that the problem of total weighted completion times is NP-hard is proved.
