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

Fang Sai-yin; Li Ming; Qiu Rong-zu

doi:10.13332/j.1000-1522.20170405

Journal of Beijing Forestry University > 2018 > 40(2): 106-113. > DOI: 10.13332/j.1000-1522.20170405

Fang Sai-yin, Li Ming, Qiu Rong-zu. Rolling horizon lot-sizing planning of wood-based panel based on an improved particle swarm optimization[J]. Journal of Beijing Forestry University, 2018, 40(2): 106-113. DOI: 10.13332/j.1000-1522.20170405

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

1.
Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China
2.
Southwest Forestry University, Kunming 650224, Yunnan, China

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Received Date: November 13, 2017
Revised Date: December 13, 2017
Published Date: January 31, 2018

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Abstract

Abstract

ObjectiveIn 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.
MethodFirstly, 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.
ResultAccording to the simulation results, to a wood-based panel production line with an annual output of 100 000 m³, 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%.
ConclusionRHP is an efficient way to make lot-sizing planning of wood-based 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.
- lot-sizing planning,
- particle swarm optimization,
- rolling horizon planning,
- wood-based panel

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[1]	Heady R B, Zhu Z W. An improved implementation of the Wagner-Whitin algorithm[J]. Production and Operations Management, 1994, 3(1):55-63.
[2]	Baltacioǧlu G, Temiz I, Erol S. Fuzzy Wagner Whitin algorithm and an application of class I supplies [J]. Gazi University Journal of Science, 2011, 24(1): 125-134. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=Open J-Gate000001025327
[3]	Fandel G, Trockel J. Investment and lot size planning in a supply chain: coordinating a just-in-time-delivery with a Harris- or a Wagner/Whitin-solution [J]. Journal of Business Economics, 2016, 86(1-2):173-195. doi: 10.1007/s11573-015-0800-6
[4]	Fu C C, Huang S Y. The maximum setup time and setup cost of achieving Just-in-Time system[J]. Journal of Business Theory and Practice, 2016, 4(1):75-84.
[5]	Sahin F, Narayanan A, Robinson E P. Rolling horizon planning in supply chains: review, implications and directions for future research[J]. International Journal of Production Research, 2013, 51(18):5413-5436. doi: 10.1080/00207543.2013.775523
[6]	Tiacci L, Saetta S. Demand forecasting, lot sizing and scheduling on a rolling horizon basis[J]. International Journal of Production Economics, 2012, 140(2):803-814. doi: 10.1016/j.ijpe.2012.02.007
[7]	Herrera C, Belmokhtar-Berraf S, Thomas A, et al. A reactive decision-making approach to reduce instability in a master production schedule[J]. International Journal of Production Research, 2016, 54(8):2394-2404. doi: 10.1080/00207543.2015.1078516
[8]	Xia H, Li X Y, Gao L. A hybrid genetic algorithm with variable neighborhood search for dynamic integrated process planning and scheduling [J]. Computers & Industrial Engineering, 2016, 102:99-112. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=ae252d1a40e3ed8bb445093d1413226b
[9]	Buer T, Homberger J, Gehring H. A collaborative ant colony metaheuristic for distributed multi-level uncapacitated lot-sizing [J]. International Journal of Production Research, 2013, 51(17):5253-5270. doi: 10.1080/00207543.2013.802822
[10]	Karimi-Nasab M, Modarres M, Seyedhoseini S M. A self-adaptive PSO for joint lot sizing and job shop scheduling with compressible process times [J]. Applied Soft Computing, 2015, 27:137-147. doi: 10.1016/j.asoc.2014.10.015
[11]	王雷, 赵秋红, 许绍云.考虑柔性检修计划的圆钢热轧批量调度[J].北京航空航天大学学报, 2016, 42(3):435-443. http://d.old.wanfangdata.com.cn/Periodical/bjhkhtdxxb201603003 Wang L, Zhao Q H, Xu S Y. Hot-rolling batch scheduling in round steel production with flexible maintenance planning [J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(3):435-443. http://d.old.wanfangdata.com.cn/Periodical/bjhkhtdxxb201603003
[12]	闫萍, 焦明海, 赵冰梅.粒子群算法在Lot-sizing问题中的应用[J].控制与决策, 2012, 27(7):1077-1081. http://d.old.wanfangdata.com.cn/Periodical/kzyjc201207022 Yan P, Jiao M H, Zhao B M. Application of particle swarm optimization algorithm in lot-sizing problem [J]. Control and Decision, 2012, 27(7):1077-1081. http://d.old.wanfangdata.com.cn/Periodical/kzyjc201207022

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