哈尔滨工程大学学报
哈爾濱工程大學學報
합이빈공정대학학보
JOURNAL OF HARBIN ENGINEERING UNIVERSITY
2014年
11期
1409-1414,1421
,共7页
江才林%陆志强%崔维伟
江纔林%陸誌彊%崔維偉
강재림%륙지강%최유위
异速并行机调度%预防性维护%整数规划%启发式算法%混合遗传算法
異速併行機調度%預防性維護%整數規劃%啟髮式算法%混閤遺傳算法
이속병행궤조도%예방성유호%정수규화%계발식산법%혼합유전산법
uniform machine scheduling%preventive maintenance%integer programming%heuristic algorithm%hy-brid genetic algorithm
针对异速并行机系统,考虑机器具有周期预防性维护的不可用约束,建立生产调度与预防性维护集成优化的混合整数规划模型。基于改进LPT的机器负载均衡技术与基于最小装箱松弛法的单机调度优化算法,设计了有效的启发式算法HCA,与Cplex的数据试验比较表明,对于中小规模问题其解与最优解或低界的百分比误差小于10%。设计了结合装箱算法的混合遗传算法HGA,与HCA对比的数据试验表明,对于大规模问题HGA表现更加优异。通过与独立决策比较的数据实验证明了生产调度与设备维护的联合决策模型效果更优,可有效协调车间生产与维修的总体计划。
針對異速併行機繫統,攷慮機器具有週期預防性維護的不可用約束,建立生產調度與預防性維護集成優化的混閤整數規劃模型。基于改進LPT的機器負載均衡技術與基于最小裝箱鬆弛法的單機調度優化算法,設計瞭有效的啟髮式算法HCA,與Cplex的數據試驗比較錶明,對于中小規模問題其解與最優解或低界的百分比誤差小于10%。設計瞭結閤裝箱算法的混閤遺傳算法HGA,與HCA對比的數據試驗錶明,對于大規模問題HGA錶現更加優異。通過與獨立決策比較的數據實驗證明瞭生產調度與設備維護的聯閤決策模型效果更優,可有效協調車間生產與維脩的總體計劃。
침대이속병행궤계통,고필궤기구유주기예방성유호적불가용약속,건립생산조도여예방성유호집성우화적혼합정수규화모형。기우개진LPT적궤기부재균형기술여기우최소장상송이법적단궤조도우화산법,설계료유효적계발식산법HCA,여Cplex적수거시험비교표명,대우중소규모문제기해여최우해혹저계적백분비오차소우10%。설계료결합장상산법적혼합유전산법HGA,여HCA대비적수거시험표명,대우대규모문제HGA표현경가우이。통과여독립결책비교적수거실험증명료생산조도여설비유호적연합결책모형효과경우,가유효협조차간생산여유수적총체계화。
A mixed integer programming model integrating the production scheduling and preventive maintenances is proposed to solve the unavailability constraints of uniform machine scheduling system problem.Specifically, a con-structive heuristic algorithm ( HCA) has been developed based on load balancing technology of improved longest processing time ( LPT) rule and single machine optimization method of minimum bin slack heuristic.The numerical experiment compared with Cplex showed that the gap between the solution of HCA and optimal solution ( low bound) is less than 10% for the small and medium scale problems.Furthermore, a hybrid genetic algorithm ( HGA) combining bin-packing algorithm is proposed.The numerical experiment compared with HCA showed that the performance of HGA is better than HCA for large scale problems.Finally, the data experiments indicated that the joint decision-making model integrating production scheduling and machine maintenance appears to perform bet-ter than the independent decision-making model, as well as coordinate the overall plan of the production and main-tenance effectively.