Double Layer Genetic Algorithm for Integrated Scheduling Optimization of Part and Tool Flows
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摘要: 为解决柔性制造系统中工件流与刀具流并存情况下的调度优化问题,以用完成时间最短为目标,建立 了工件流灢刀具流综合调度数学模型,提出了双重遗传算法并对模型进行优化求解.外层遗传优化求解可行工序 加工序列,内层遗传优化进行最优可行刀具分派方案的搜索,搜索结果的适应度则作为外层优化解的评判标准. 实例分析结果表明:双重遗传算法在取得各工件优化排序的同时,还获取了各类刀具的优化分派,与传统的规则 调度相比,系统的完工时间及等刀时间分别减少了19.7%和20.4%.Abstract: To solve the schedule optimization problem involving both part flow and tool flow in an FMS (flexible manufacturing system), a mathematical model of integrated scheduling for part and tool flows was presented, in which the objective was to minimize system make-span. A double-layer GA (genetic algorithm) was proposed for global optimization of the model. The outer and the inner layers of the GA were to search optimal and feasible operation sequences and tool assignment, respectively, and the fitness of the tool assignment was used to evaluate the outer layer optimization. A case study shown that the system make-span and waiting the time for tools were reduced by 19.7% and 20.4%, respectively, using the proposed double-layer GA compared with those obtained using heuristic rules.
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Key words:
- flexible manufacturing system /
- tool flow /
- part flow /
- genetic algorithm /
- schedule
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