Dynamic dispatching priority setting in customer-oriented manufacturing environments

被引:0
作者
Hülya Güçdemir
Hasan Selim
机构
[1] Manisa Celal Bayar University,Department of Industrial Engineering
[2] Dokuz Eylul University,Department of Industrial Engineering
来源
The International Journal of Advanced Manufacturing Technology | 2017年 / 92卷
关键词
Job shop scheduling; Customer satisfaction; Dynamic priority setting; Simulation optimization;
D O I
暂无
中图分类号
学科分类号
摘要
In today’s competitive environment, customer-oriented view is essential in gaining sustainable competitive advantage. This study aims to reflect the customer-oriented view to production planning and control decisions. To this aim, a simulation optimization-based approach is developed for job shop systems with dynamic order arrivals. Product-type-based lot splitting is applied in order to improve the flow time, and machine-based dispatching rules are utilized for sublot scheduling to realize dynamic scheduling. Multiple customer segments with different importance weights and their expectations and penalties on order completion rate on due date, tardiness, and earliness are considered. A customer satisfaction-based objective function is defined. Customer-oriented dispatching rules are proposed in this study to ensure the prioritization of orders from the key customers in order fulfilling. In order to prevent customer losses by providing a balanced structure between the customer segments in terms of the satisfaction levels, weight setting functions that dynamically compute the weights in the proposed dispatching rules are proposed. It is aimed to determine the near-optimal values of the segment-based parameters of the related weight setting functions. To this aim, a differential evolution algorithm-based simulation optimization approach is proposed. To confirm its viability, the proposed approach is applied to a realistic job shop system.
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收藏
页码:1861 / 1874
页数:13
相关论文
共 97 条
[1]  
Paiva EL(2010)Manufacturing and marketing integration from a cumulative capabilities perspective Int J Prod Econ 126 379-386
[2]  
Güçdemir H(2015)Integrating multi-criteria decision making and clustering for business customer segmentation Ind Manag Data Syst 115 1022-1040
[3]  
Selim H(2014)A dispatching algorithm for flexible job shop scheduling with transfer batches: an industrial application Prod Plan Cont 25 93-109
[4]  
Calleja G(2014)Order allocation for multiple supply-demand networks within a cluster J Intell Manuf 25 1367-1376
[5]  
Pastor R(2016)Heuristic approaches for scheduling jobs in large-scale flexible job shops Comp Oper Res 68 97-109
[6]  
Xiang W(1996)Job shop scheduling by local search INFORMS J on Comput 8 302-317
[7]  
Song F(2006)Job shop scheduling techniques in semiconductor manufacturing Int J Adv Manuf Technol 27 1163-1169
[8]  
Ye F(2015)A research survey: review of AI solution strategies of job shop scheduling problem J Intell Manuf 26 961-973
[9]  
Sobeyko O(2016)A review on job shop scheduling with setup times Proceed of the Inst of Mech Eng, Part B: J Eng Manuf 230 517-533
[10]  
Mönch L(2009)Performance of an ant colony optimization algorithm in dynamic job shop scheduling problems Int J Prod Res 47 2903-2920