To generate a test set for a given circuit (including both combinational and sequential circuits), choice of an algorithm within a number of existing test generation algorithms to apply is bound to vary from circuit t...To generate a test set for a given circuit (including both combinational and sequential circuits), choice of an algorithm within a number of existing test generation algorithms to apply is bound to vary from circuit to circuit. In this paper, the genetic algorithms are used to construct the models of existing test generation algorithms in making such choice more easily. Therefore, we may forecast the testability parameters of a circuit before using the real test generation algorithm. The results also can be used to evaluate the efficiency of the existing test generation algorithms. Experimental results are given to convince the readers of the truth and the usefulness of this approach.展开更多
This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the ...This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the total distance. This problem exists widely in real-life logistics distribution process.We propose a hybrid column generation algorithm(HCGA) for the OVRPTW, embedding both exact algorithm and metaheuristic. In HCGA, a label setting algorithm and an intelligent algorithm are designed to select columns from small and large subproblems, respectively. Moreover, a branch strategy is devised to generate the final feasible solution for the OVRPTW. The computational results show that the proposed algorithm has faster speed and can obtain the approximate optimal solution of the problem with 100 customers in a reasonable time.展开更多
This paper deals with the target-fault-oriented test generation of sequential circuits using genetic algorithms. We adopted the concept of multiple phases and proposed four sub-procedures which consist of activation, ...This paper deals with the target-fault-oriented test generation of sequential circuits using genetic algorithms. We adopted the concept of multiple phases and proposed four sub-procedures which consist of activation, propagation and justification phases. The paper focuses on the design of genetic operators and construction of fitness functions which are based on the structure information of circuits. Using ISCAS89 benchmarks, the experiment results of GA were given.展开更多
A novel multi-chip module(MCM) interconnect test generation scheme based on ant algorithm(AA) with mutation operator was presented.By combing the characteristics of MCM interconnect test generation,the pheromone updat...A novel multi-chip module(MCM) interconnect test generation scheme based on ant algorithm(AA) with mutation operator was presented.By combing the characteristics of MCM interconnect test generation,the pheromone updating rule and state transition rule of AA is designed.Using mutation operator,this scheme overcomes ordinary AA’s defects of slow convergence speed,easy to get stagnate,and low ability of full search.The international standard MCM benchmark circuit provided by the MCNC group was used to verify the approach.The results of simulation experiments,which compare to the results of standard ant algorithm,genetic algorithm(GA) and other deterministic interconnecting algorithms,show that the proposed scheme can achieve high fault coverage,compact test set and short CPU time,that it is a newer optimized method deserving research.展开更多
With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally...With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field （APF） method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.展开更多
基金This work was supported by National Natural Science Foundation of China (NSFC) under the grant !No. 69873030
文摘To generate a test set for a given circuit (including both combinational and sequential circuits), choice of an algorithm within a number of existing test generation algorithms to apply is bound to vary from circuit to circuit. In this paper, the genetic algorithms are used to construct the models of existing test generation algorithms in making such choice more easily. Therefore, we may forecast the testability parameters of a circuit before using the real test generation algorithm. The results also can be used to evaluate the efficiency of the existing test generation algorithms. Experimental results are given to convince the readers of the truth and the usefulness of this approach.
基金supported by the National Natural Science Foundation of China (61963022,51665025,61873328)。
文摘This paper addresses the open vehicle routing problem with time window(OVRPTW), where each vehicle does not need to return to the depot after completing the delivery task.The optimization objective is to minimize the total distance. This problem exists widely in real-life logistics distribution process.We propose a hybrid column generation algorithm(HCGA) for the OVRPTW, embedding both exact algorithm and metaheuristic. In HCGA, a label setting algorithm and an intelligent algorithm are designed to select columns from small and large subproblems, respectively. Moreover, a branch strategy is devised to generate the final feasible solution for the OVRPTW. The computational results show that the proposed algorithm has faster speed and can obtain the approximate optimal solution of the problem with 100 customers in a reasonable time.
文摘This paper deals with the target-fault-oriented test generation of sequential circuits using genetic algorithms. We adopted the concept of multiple phases and proposed four sub-procedures which consist of activation, propagation and justification phases. The paper focuses on the design of genetic operators and construction of fitness functions which are based on the structure information of circuits. Using ISCAS89 benchmarks, the experiment results of GA were given.
文摘A novel multi-chip module(MCM) interconnect test generation scheme based on ant algorithm(AA) with mutation operator was presented.By combing the characteristics of MCM interconnect test generation,the pheromone updating rule and state transition rule of AA is designed.Using mutation operator,this scheme overcomes ordinary AA’s defects of slow convergence speed,easy to get stagnate,and low ability of full search.The international standard MCM benchmark circuit provided by the MCNC group was used to verify the approach.The results of simulation experiments,which compare to the results of standard ant algorithm,genetic algorithm(GA) and other deterministic interconnecting algorithms,show that the proposed scheme can achieve high fault coverage,compact test set and short CPU time,that it is a newer optimized method deserving research.
基金supported by the National Outstanding Youth Science Foundation (60925011)the National Natural Science Foundation of China (61203181)
文摘With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field （APF） method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.
