哈尔滨工程大学学报
哈爾濱工程大學學報
합이빈공정대학학보
JOURNAL OF HARBIN ENGINEERING UNIVERSITY
2013年
8期
1034-1044
,共11页
张志英%李广照%顾炜%隋意
張誌英%李廣照%顧煒%隋意
장지영%리엄조%고위%수의
钢板切割%时间约束%多功能%best-fit策略
鋼闆切割%時間約束%多功能%best-fit策略
강판절할%시간약속%다공능%best-fit책략
sted plates cutting%time-constraint%multifunction%best-fit strategy
针对船舶建造中钢板利用率和零件理料效率低等问题,建立带时间属性的多功能钢板切割作业计划优化模型。该模型综合考虑切割机类型、切割机能力、零件切割时间以及零件在钢板中排放等约束条件,目标是最大化各类型切割机下的钢板利用率。首先,利用启发式算法将所有分段零件进行重组,再采用基于BF( best-fit)策略的启发式算法对模型进行求解。最后以某船厂的分段钢板切割为例,获得各类型切割机的零件切割周计划任务量,通过设置各类零件集合的子切割能力来获得最优的切割计划。结果表明,在满足生产计划和切割机等约束下,该算法相对于BL( bottom-lift)、BLF ( bottom-lift fit)和GA( genetic algorithm)算法能获得更高的钢板利用率和更好的切割计划,具有实用性和有效性。
針對船舶建造中鋼闆利用率和零件理料效率低等問題,建立帶時間屬性的多功能鋼闆切割作業計劃優化模型。該模型綜閤攷慮切割機類型、切割機能力、零件切割時間以及零件在鋼闆中排放等約束條件,目標是最大化各類型切割機下的鋼闆利用率。首先,利用啟髮式算法將所有分段零件進行重組,再採用基于BF( best-fit)策略的啟髮式算法對模型進行求解。最後以某船廠的分段鋼闆切割為例,穫得各類型切割機的零件切割週計劃任務量,通過設置各類零件集閤的子切割能力來穫得最優的切割計劃。結果錶明,在滿足生產計劃和切割機等約束下,該算法相對于BL( bottom-lift)、BLF ( bottom-lift fit)和GA( genetic algorithm)算法能穫得更高的鋼闆利用率和更好的切割計劃,具有實用性和有效性。
침대선박건조중강판이용솔화령건리료효솔저등문제,건립대시간속성적다공능강판절할작업계화우화모형。해모형종합고필절할궤류형、절할궤능력、령건절할시간이급령건재강판중배방등약속조건,목표시최대화각류형절할궤하적강판이용솔。수선,이용계발식산법장소유분단령건진행중조,재채용기우BF( best-fit)책략적계발식산법대모형진행구해。최후이모선엄적분단강판절할위례,획득각류형절할궤적령건절할주계화임무량,통과설치각류령건집합적자절할능력래획득최우적절할계화。결과표명,재만족생산계화화절할궤등약속하,해산법상대우BL( bottom-lift)、BLF ( bottom-lift fit)화GA( genetic algorithm)산법능획득경고적강판이용솔화경호적절할계화,구유실용성화유효성。
An optimization model for multifunctional steel plate cutting planning with time attribute was developed to solve the problems of low steel plate utilization and parts distribution efficiency. Taking into account a variety of fac-tors, such as cutting machine type, cutting capacity, parts cutting time, and parts distribution in steel plate, the objective of the model is to maximize steel plate utilization of all kinds of cutting machines. First, a heuristic algo-rithm was used to reset all parts of ship blocks and then a heuristic algorithm based on BF ( best-fit) strategy was presented to solve the model. Finally, we take an example of a ship-block cutting task in a shipyard, and gain weekly cutting assignments of different types of machines. The optimal cutting planning was determined by setting up the optimal sub-cutting capacity for each set of parts. The result shows, compared to some algorithms, such as BL (bottom-lift), BLF (bottom-lift fit) and GA (genetic algorithm), the proposed method satisfying constraints such as production plan and cutting machine type, is practical and effective in terms of obtaining higher steel plate utilization and better cutting planning.