Scheduling problem in seru production system considering DeJong’s learning effect and job splitting

2022 ◽  
Author(s):  
Zhe Zhang ◽  
Xiaoling Song ◽  
Huijun Huang ◽  
Yong Yin ◽  
Benjamin Lev
Keyword(s):  
Production System ◽  
Learning Effect ◽  
Scheduling Problem ◽  
Job Splitting

An order scheduling problem with position-based learning effect

2016 ◽  
Vol 74 ◽  
pp. 175-186 ◽  
Author(s):  
Jianyou Xu ◽  
Chin-Chia Wu ◽  
Yunqiang Yin ◽  
Chuanli Zhao ◽  
Yi-Tang Chiou ◽  
...  
Keyword(s):  
Learning Effect ◽  
Scheduling Problem ◽  
Order Scheduling

scholarly journals Scheduling Jobs Families with Learning Effect on the Setup

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Sergio Fichera ◽  
Antonio Costa ◽  
Fulvio Cappadonna
Keyword(s):  
Completion Time ◽  
Learning Effect ◽  
Flow Shop ◽  
Group Scheduling ◽  
Scheduling Problem ◽  
Learning Effects ◽  
Anova Analysis ◽  
Hybrid Metaheuristic ◽  
Set Up ◽  
Over Time

The present paper aims to address the flow-shop sequence-dependent group scheduling problem with learning effect (FSDGSLE). The objective function to be minimized is the total completion time, that is, the makespan. The workers are required to carry out manually the set-up operations on each group to be loaded on the generic machine. The operators skills improve over time due to the learning effects; therefore the set-up time of a group under learning effect decreases depending on the order the group is worked in. In order to effectively cope with the issue at hand, a mathematical model and a hybrid metaheuristic procedure integrating features from genetic algorithms (GA) have been developed. A well-known problem benchmark risen from literature, made by two-, three- and six-machine instances, has been taken as reference for assessing performances of such approach against the two most recent algorithms presented by literature on the FSDGS issue. The obtained results, also supported by a properly developed ANOVA analysis, demonstrate the superiority of the proposed hybrid metaheuristic in tackling the FSDGSLE problem under investigation.

Models for Solving Integrated Planning and Scheduling Problem: Computational Comparison

2018 ◽  
Vol 34 ◽  
pp. 161-170 ◽  
Author(s):  
Zineb Ibn Majdoub Hassani ◽  
Abdellah El Barkany ◽  
Abdelouahhab Jabri ◽  
Ikram El Abbassi
Keyword(s):  
Production Planning ◽  
Production System ◽  
Production Plan ◽  
Scheduling Problem ◽  
Integrated Planning ◽  
System Planning ◽  
Planning And Scheduling ◽  
Computational Comparison

This article concerns the integration of planning and scheduling production system. Planning and scheduling are usually treated separately because of their complexity. Scheduling largely depends on the production quantities computed at the production planning level. However, ignoring scheduling constraints in the tactical level leads to inconsistent decisions. So, it is important to integrate planning and scheduling to efficiently manage operations and to determine a realistic production plan for a given sequence of jobs on each machine. In this paper, we present some approaches proposed to solve the problem and we realize a comparison between the two most interesting ones, using the standard solver CPLEX.

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