Buffer influences the performance of production lines greatly.To solve the buffer allocation problem(BAP) in serial production lines with unreliable machines effectively,an optimization method is proposed based on an ...Buffer influences the performance of production lines greatly.To solve the buffer allocation problem(BAP) in serial production lines with unreliable machines effectively,an optimization method is proposed based on an improved ant colony optimization(IACO) algorithm.Firstly,a problem domain describing buffer allocation is structured.Then a mathematical programming model is established with an objective of maximizing throughput rate of the production line.On the basis of the descriptions mentioned above,combining with a two-opt strategy and an acceptance probability rule,an IACO algorithm is built to solve the BAP.Finally,the simulation experiments are designed to evaluate the proposed algorithm.The results indicate that the IACO algorithm is valid and practical.展开更多
Some unsafe languages,like C and C++,let programmers maximize performance but are vulnerable to memory errors which can lead to program crashes and unpredictable behavior.Aiming to solve the problem,traditional memory...Some unsafe languages,like C and C++,let programmers maximize performance but are vulnerable to memory errors which can lead to program crashes and unpredictable behavior.Aiming to solve the problem,traditional memory allocating strategy is improved and a new probabilistic memory allocation technology is presented.By combining random memory allocating algorithm and virtual memory,memory errors are avoided in all probability during software executing.By replacing default memory allocator to manage allocation of heap memory,buffer overflows and dangling pointers are prevented.Experiments show it is better than Diehard of the following aspects:memory errors prevention,performance in memory allocation set and ability of controlling working set.So probabilistic memory allocation is a valid memory errors prevention technology and it can tolerate memory errors and provide probabilistic memory safety effectively.展开更多
基金Supported by the National Natural Science Foundation of China(No.61273035,71471135)
文摘Buffer influences the performance of production lines greatly.To solve the buffer allocation problem(BAP) in serial production lines with unreliable machines effectively,an optimization method is proposed based on an improved ant colony optimization(IACO) algorithm.Firstly,a problem domain describing buffer allocation is structured.Then a mathematical programming model is established with an objective of maximizing throughput rate of the production line.On the basis of the descriptions mentioned above,combining with a two-opt strategy and an acceptance probability rule,an IACO algorithm is built to solve the BAP.Finally,the simulation experiments are designed to evaluate the proposed algorithm.The results indicate that the IACO algorithm is valid and practical.
基金supported by the Natural Science Foundation of China under Grant No.61100205the National High-Tech Research and Development Plan of China under Grant No.2009AA01Z433the Project of the Fundamental Research Funds of Beijing Institute of Technology
文摘Some unsafe languages,like C and C++,let programmers maximize performance but are vulnerable to memory errors which can lead to program crashes and unpredictable behavior.Aiming to solve the problem,traditional memory allocating strategy is improved and a new probabilistic memory allocation technology is presented.By combining random memory allocating algorithm and virtual memory,memory errors are avoided in all probability during software executing.By replacing default memory allocator to manage allocation of heap memory,buffer overflows and dangling pointers are prevented.Experiments show it is better than Diehard of the following aspects:memory errors prevention,performance in memory allocation set and ability of controlling working set.So probabilistic memory allocation is a valid memory errors prevention technology and it can tolerate memory errors and provide probabilistic memory safety effectively.
