基于微粒群优化算法的人造板生产批量时域滚动计划

Rolling horizon lot-sizing planning of wood-based panel based on an improved particle swarm optimization

【目的】生产批量计划是企业制定主令生产计划和物料需求计划的依据,生产批量计划的优化也是企业节约成本和原料的关键所在。目前人造板企业都采用批量生产模式,并且依据事先设定的生产计划确定各个阶段的生产任务,但随着市场竞争的日益激励和个性化需求的提高,每个阶段的实际生产任务通常需要根据市场需求及时调整。为此,针对人造板生产批量计划问题,提出基于微粒群优化算法(PSO)的时域滚动计划。【方法】首先,根据人造板批量生产特点,制定决策变量和约束条件,建立生产批量计划的混合整数决策模型。然后依据决策模型的约束条件,采用降维搜索的方式,提出改进的微粒群求解算法。最后,采用时域滚动计划进行模拟仿真。【结果】仿真结果表明:对于年产10万m3的刨花板生产线而言,以3个月作为一个滚动计划单元,在12个月的生产批量计划中,采用改进PSO算法获得的生产批量计划可以节约1.8%的成本,有生产能力约束时可以节约近0.9%的成本。【结论】对于人造板批量生产模式,时域滚动计划能够使得生产计划动态满足市场需求,同时时域滚动计划模型是一类非确定性(NP)困难问题,智能群集优化算法为此类问题的求解提供了较好的解决途径。未来的研究可以关注生产批量计划问题数学模型的完善以及智能优化算法设计方面。

[Objective]In general,lot-sizing planning（LSP） is the basis of master production schedule and material requirements planning.Obviously,optimization of LSP is the key to save cost and materials.At present,bulk-production mode is widely adopted in wood-based panel industries.For arranging the productive task,the detail planning needs to be made in advance.However,the scheduled planning usually needs to be re-planned to cope with the change of market requirement dynamically.For this reason,an improved particle swarm optimization（PSO） and a kind of rolling horizon planning（RHP）method are proposed to solve the LSP problem of wood-based panels in this paper.[Method]Firstly,according to the characters of production process,a series of decision variables and constrains were determined,and then,a mathematical mixed integer decision method was built for LSP problem.Secondly,an improved PSO algorithm was designed by reducing the dimension of the solution space.At last,with RHP method,the improved PSO algorithm was used to solve a series of sub-LSP problems repeatedly.A simulation example was designed to verify the performance of the LSP model and improve PSO algorithm.[Result]According to the simulation results,to a wood-based panel production line with an annual output of 100 000 m^3,when the planning horizon and total planning period were set to 3 months and 12 months respectively,1.8% production cost could be saved through RHP method and the improved PSO approach.In addition,to the same model with production capacity constrains,the production cost could be reduced by 0.9%.[Conclusion]RHP is an efficient way to make lot-sizing planning of woodbased panel.The important advantage of RHP is that the production schedule could be adjusted with the changing market requirement dynamically.Due to the NP-hard of RHP,the intelligent swarm optimizations could solve these problems with an acceptable period of time.In addition,future research will focus on the model of LSP with actual constrains and the algorithms of intelligent swarm optimization.