To solve the sequencing problem in mixed-model flexible assembly lines (MMFALs) with variable launching intervals, a mathematical model aiming to minimize the cost of utility and idle times is developed. To obtain hig...To solve the sequencing problem in mixed-model flexible assembly lines (MMFALs) with variable launching intervals, a mathematical model aiming to minimize the cost of utility and idle times is developed. To obtain high-quality sequences, an advanced scatter search (ASS) algorithm is proposed. A heuristic approach, i.e. launching intervals between products algorithm (LIBPA), is incorporated into the ASS algorithm to solve the launching interval problem for each sequence. Numerical experiments with different scales are conducted to compare the performance of ASS with genetic algorithm (GA). In addition, we compare the cost of variable launching intervals approach with fixed launching intervals approach. The results indicate that the ASS is efficient and effective, and considering variable launching intervals in mixed-model assembly lines (MMALs) sequencing problem can improve the performance of the line.展开更多
Shuffled frog leaping algorithm( SFLA) was used to solve multi-objective sequencing problem of mixed model assembly line( MMAL). Local convergence can be avoided and optimal solution can be obtained to a certain exten...Shuffled frog leaping algorithm( SFLA) was used to solve multi-objective sequencing problem of mixed model assembly line( MMAL). Local convergence can be avoided and optimal solution can be obtained to a certain extent. However,the multi-objective sequencing problem of MMAL is an non-deterministic polynomial hard( NP-hard) problem and the shortcomings are slow convergence rate and low precision. To solve the shortcomings for optimization objectives of minimizing total utility time and keeping average consumption rate of parts, a chaos differential evolution SFLA( CDESFLA) is proposed in this study. Because SFLA is easy to fall into local optimum,the evolution operator of differential evolution algorithms is introduced in SFLA as a local search strategy,and differential mutation operator is introduced in chaotic sequence to prevent premature convergence. The examples show that the proposed CDESFLA is better for convergence accuracy than SFLA,genetic algorithm( GA) and particle swarm optimization( PSO)展开更多
基金the National Natural Science Foundation of China(No.71071115)the National High Technology Research and Development Program (863) of China(No.2009AA043000)
文摘To solve the sequencing problem in mixed-model flexible assembly lines (MMFALs) with variable launching intervals, a mathematical model aiming to minimize the cost of utility and idle times is developed. To obtain high-quality sequences, an advanced scatter search (ASS) algorithm is proposed. A heuristic approach, i.e. launching intervals between products algorithm (LIBPA), is incorporated into the ASS algorithm to solve the launching interval problem for each sequence. Numerical experiments with different scales are conducted to compare the performance of ASS with genetic algorithm (GA). In addition, we compare the cost of variable launching intervals approach with fixed launching intervals approach. The results indicate that the ASS is efficient and effective, and considering variable launching intervals in mixed-model assembly lines (MMALs) sequencing problem can improve the performance of the line.
基金National Natural Science Foundation of China(o.61370037)
文摘Shuffled frog leaping algorithm( SFLA) was used to solve multi-objective sequencing problem of mixed model assembly line( MMAL). Local convergence can be avoided and optimal solution can be obtained to a certain extent. However,the multi-objective sequencing problem of MMAL is an non-deterministic polynomial hard( NP-hard) problem and the shortcomings are slow convergence rate and low precision. To solve the shortcomings for optimization objectives of minimizing total utility time and keeping average consumption rate of parts, a chaos differential evolution SFLA( CDESFLA) is proposed in this study. Because SFLA is easy to fall into local optimum,the evolution operator of differential evolution algorithms is introduced in SFLA as a local search strategy,and differential mutation operator is introduced in chaotic sequence to prevent premature convergence. The examples show that the proposed CDESFLA is better for convergence accuracy than SFLA,genetic algorithm( GA) and particle swarm optimization( PSO)
