Three heuristic algorithms for optimal polygonal approximation of digital planar curves is presented. With Genetic Algorithm (GA), improved Genetic Algorithm (IGA) based on Pareto optimal solution and Tabu Search (TS)...Three heuristic algorithms for optimal polygonal approximation of digital planar curves is presented. With Genetic Algorithm (GA), improved Genetic Algorithm (IGA) based on Pareto optimal solution and Tabu Search (TS), a near optimal polygonal approximation was obtained. Compared to the famous Teh chin algorithm, our algorithms have obtained the approximated polygons with less number of vertices and less approximation error. Compared to the dynamic programming algorithm, the processing time of our algorithms are much less expensive.展开更多
The optimal allocation of regulators banks in distribution systems is a merely combinatorial problem in which the best points of installation correspond to the best benefit, considering the admitted objective function...The optimal allocation of regulators banks in distribution systems is a merely combinatorial problem in which the best points of installation correspond to the best benefit, considering the admitted objective function, without violating and operating limits. The objective function must be chosen so that its value represents the operation state of the system. As the problem possesses combinatorial nature, its complexity will increase exponentially with the number of possibilities. Systems with large numbers of nodes and / or with the possibility of installing more than one bank require a large number of calculations to find the solution. An additional issue is the fact that the problem does not have a continuous nature, presenting discontinuity points in the objective function, limiting the application of optimization methods based on gradients. Based on the nature of the problem two optimization methods were used to solve the problem: Genetic Algorithm (GA) and modified Tabu Search (TS). The GA function will scour the search space and find regions with local minima that are candidates to be the solution. On the other hand the TS provides local search in the regions defined by GA so that the overall optimum is achieved.展开更多
A local improvement procedure based on tabu search(TS) was incorporated into a basic genetic algorithm(GA) and a global optimal algorithm,i.e.,hybrid genetic algorithm(HGA) approach was used to search the circular and...A local improvement procedure based on tabu search(TS) was incorporated into a basic genetic algorithm(GA) and a global optimal algorithm,i.e.,hybrid genetic algorithm(HGA) approach was used to search the circular and noncircular slip surfaces associated with their minimum safety factors.The slope safety factors of circular and noncircular critical slip surfaces were calculated by the simplified Bishop method and an improved Morgenstern-Price method which can be conveniently programmed,respectively.Comparisons with other methods were made which indicate the high efficiency and accuracy of the HGA approach.The HGA approach was used to calculate one case example and the results demonstrated its applicability to practical engineering.展开更多
目的挖掘喜炎平注射液治疗儿童肺炎核心联用药物方案的临床应用规律,为探索临床不同诊疗思路、用药经验和提高中医药临床证据的循证等级提供参考。方法本研究基于全国29家医院信息管理系统(Hospital Information System,HIS)儿童肺炎的...目的挖掘喜炎平注射液治疗儿童肺炎核心联用药物方案的临床应用规律,为探索临床不同诊疗思路、用药经验和提高中医药临床证据的循证等级提供参考。方法本研究基于全国29家医院信息管理系统(Hospital Information System,HIS)儿童肺炎的用药数据,运用Tabu禁忌搜索算法,对真实世界喜炎平注射液治疗儿童肺炎人群的联合用药情况进行回顾性数据挖掘分析。结果在核心联用西药方面,抗感染治疗可以联用青霉素/美洛西林/阿莫西林、头孢呋辛/头孢曲松/头孢替安、阿奇霉素等;对症治疗可以联用对乙酰氨基酚/布洛芬、氨溴索+布地奈德+沙丁胺醇等;并发症治疗可以联用水合氯醛+苯巴比妥、磷酸肌酸+抗坏血酸等。在核心联用中药方面,可以联用小柴胡颗粒/小儿柴桂退热颗粒+鼻渊通窍颗粒、热毒宁注射液/蓝芩口服液/连花清瘟胶囊+开喉剑喷雾剂/口腔炎喷雾剂/双料喉风散、小儿肺咳颗粒+醒脾养儿颗粒/四磨汤口服液等。结论本研究的喜炎平注射液核心联用中西药方案,基本符合相关指南及诊疗规范,为优化临床联合用药、合理用药提供了一定的指导和参考。建议临床实际应用过程中,根据患儿的疾病进展情况,合理评估临床联合用药方案的疗效及安全性,注意用药配伍禁忌。展开更多
In order to deliver a complete reliable software product, testing is performed. As testing phase carries on, cost of testing process increases and it directly affects the overall project cost. Many a times it happens ...In order to deliver a complete reliable software product, testing is performed. As testing phase carries on, cost of testing process increases and it directly affects the overall project cost. Many a times it happens that the actual cost becomes more than the estimated cost. Cost is considered as the most important parameter with respect to software testing, in software industry. In recent year’s researchers have done a variety of work in the area of Cost optimization by using various concepts like Genetic Algorithm, simulated annealing and Automation in generation of test data etc. This paper proposes an efficient cost effective approach for optimizing the cost of testing using Tabu Search (TS), which will provide maximum code coverage along with the concepts of Dijkstra’s Algorithm which will be implemented in Aspiration criteria of Tabu Search in order to optimize the cost and generate a minimum cost path with maximum coverage.展开更多
文摘Three heuristic algorithms for optimal polygonal approximation of digital planar curves is presented. With Genetic Algorithm (GA), improved Genetic Algorithm (IGA) based on Pareto optimal solution and Tabu Search (TS), a near optimal polygonal approximation was obtained. Compared to the famous Teh chin algorithm, our algorithms have obtained the approximated polygons with less number of vertices and less approximation error. Compared to the dynamic programming algorithm, the processing time of our algorithms are much less expensive.
文摘The optimal allocation of regulators banks in distribution systems is a merely combinatorial problem in which the best points of installation correspond to the best benefit, considering the admitted objective function, without violating and operating limits. The objective function must be chosen so that its value represents the operation state of the system. As the problem possesses combinatorial nature, its complexity will increase exponentially with the number of possibilities. Systems with large numbers of nodes and / or with the possibility of installing more than one bank require a large number of calculations to find the solution. An additional issue is the fact that the problem does not have a continuous nature, presenting discontinuity points in the objective function, limiting the application of optimization methods based on gradients. Based on the nature of the problem two optimization methods were used to solve the problem: Genetic Algorithm (GA) and modified Tabu Search (TS). The GA function will scour the search space and find regions with local minima that are candidates to be the solution. On the other hand the TS provides local search in the regions defined by GA so that the overall optimum is achieved.
基金Project(50878082)supported by the National Natural Science Foundation of ChinaProject(2012C21058)supported by the Public Welfare Technology Application Research of Zhejiang Province,China
文摘A local improvement procedure based on tabu search(TS) was incorporated into a basic genetic algorithm(GA) and a global optimal algorithm,i.e.,hybrid genetic algorithm(HGA) approach was used to search the circular and noncircular slip surfaces associated with their minimum safety factors.The slope safety factors of circular and noncircular critical slip surfaces were calculated by the simplified Bishop method and an improved Morgenstern-Price method which can be conveniently programmed,respectively.Comparisons with other methods were made which indicate the high efficiency and accuracy of the HGA approach.The HGA approach was used to calculate one case example and the results demonstrated its applicability to practical engineering.
文摘目的挖掘喜炎平注射液治疗儿童肺炎核心联用药物方案的临床应用规律,为探索临床不同诊疗思路、用药经验和提高中医药临床证据的循证等级提供参考。方法本研究基于全国29家医院信息管理系统(Hospital Information System,HIS)儿童肺炎的用药数据,运用Tabu禁忌搜索算法,对真实世界喜炎平注射液治疗儿童肺炎人群的联合用药情况进行回顾性数据挖掘分析。结果在核心联用西药方面,抗感染治疗可以联用青霉素/美洛西林/阿莫西林、头孢呋辛/头孢曲松/头孢替安、阿奇霉素等;对症治疗可以联用对乙酰氨基酚/布洛芬、氨溴索+布地奈德+沙丁胺醇等;并发症治疗可以联用水合氯醛+苯巴比妥、磷酸肌酸+抗坏血酸等。在核心联用中药方面,可以联用小柴胡颗粒/小儿柴桂退热颗粒+鼻渊通窍颗粒、热毒宁注射液/蓝芩口服液/连花清瘟胶囊+开喉剑喷雾剂/口腔炎喷雾剂/双料喉风散、小儿肺咳颗粒+醒脾养儿颗粒/四磨汤口服液等。结论本研究的喜炎平注射液核心联用中西药方案,基本符合相关指南及诊疗规范,为优化临床联合用药、合理用药提供了一定的指导和参考。建议临床实际应用过程中,根据患儿的疾病进展情况,合理评估临床联合用药方案的疗效及安全性,注意用药配伍禁忌。
文摘In order to deliver a complete reliable software product, testing is performed. As testing phase carries on, cost of testing process increases and it directly affects the overall project cost. Many a times it happens that the actual cost becomes more than the estimated cost. Cost is considered as the most important parameter with respect to software testing, in software industry. In recent year’s researchers have done a variety of work in the area of Cost optimization by using various concepts like Genetic Algorithm, simulated annealing and Automation in generation of test data etc. This paper proposes an efficient cost effective approach for optimizing the cost of testing using Tabu Search (TS), which will provide maximum code coverage along with the concepts of Dijkstra’s Algorithm which will be implemented in Aspiration criteria of Tabu Search in order to optimize the cost and generate a minimum cost path with maximum coverage.
