摘要
针对无等待流水线调度问题提出了一种混合离散化粒子群优化算法。通过建立位置矢量编码与调度方案之间的映射关系将连续的粒子群优化算法应用于离散的无等待流水线工件调度问题。为了提高离散粒子群算法的性能,增强算法的探索能力,在粒子群每次迭代之后对全局最优解加入随机扰动并进行变邻域搜索。仿真结果表明,该优化算法具有良好的性能。
In this paper, no-wait flow shops scheduling problems for a mixed discrete particle swarm optimization, through the establishment of the location of the vector encoding and scheduling program of mapping relations between the continuous particle swarm optimization algorithm is applied to discrete no-wait flow shops scheduling problem. In order to improve the discrete PSO performance, enhanced ability to explore algorithm in particle swarm after each iteration of the global optimal solution by adding random perturbation and variable neighborhood search. Simulation results show that the optimization algorithm has a good performance.
出处
《上海第二工业大学学报》
2009年第1期6-11,共6页
Journal of Shanghai Polytechnic University
基金
上海市教育委员会高校人才培养工程建设项目资助
关键词
无等待流水线调度
离散粒子群优化算法
变邻域搜索
no-wait flow shops scheduling
discrete particle swarm optimization
variable neighborhood search