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Energy Saving Scheduling of A Single Machine System Based on Bi-objective Particle Swarm Optimization*

机译:基于双目标粒子群优化的单机系统的节能调度 *

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Energy cost becomes an important performance indicator of a production process. A great deal of energy is wasted because of the idle period resulted from the unreasonable schedule of jobs and machines. Energy consumption and other performance indicators should be combined to optimize the production schedule in shop floor. A single machine scheduling optimization problem is considered in this study, where assume that jobs are arrived at different time. An optimization model with bi-objective is formulated for minimizing the total energy consumption and the total tardiness during a shift production. Based on sequence encoding of job-machine schedule in two dimensions, a particle swarm optimization method is proposed to search Pareto solutions of the model. External archive technology is adopted to store and maintenance the non-dominated schedules. A grid density method is used to update the global best solution so far for the construction of the next generation populations. A case study is given to show the effectiveness of the algorithm based on the Pareto solutions.
机译:能源成本成为生产过程的重要表现指标。由于空闲时期,浪费了大量的能量,因此由无理的工作和机器的时间表产生。应组合能源消耗和其他绩效指标,以优化车间生产计划。在本研究中考虑了单一机器调度优化问题,假设作业在不同的时间到达。具有双目标的优化模型,可为最小化换档生产过程中的总能耗和总迟到。基于两个维度的作业机时间表的序列编码,提出了一种粒子群优化方法来搜索模型的Pareto解决方案。采用外部存档技术来存储和维护非主导的计划。迄今为止,使用网格密度方法来更新全球最佳解决方案,以便建设下一代人口。给出了基于Pareto解决方案的算法的案例研究。

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