Evaluation of Simulation-Based Optimization in Grafting Labor Allocation

Masoud, Sara; Son, Young-Jun; Kubota, Chieri; Tronstad, Russell

doi:10.13031/aea.12487

Cited by 10 publications

(3 citation statements)

References 26 publications

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“…In addition, the implementation of DDDAS paradigm in this framework and the fidelity level optimization of the dynamic decision making is discussed here . The planning unit relies on the concept of simulation-based optimization where simulation mimics the performance of the system under study through the estimated parameters provided by the measuring unit, and optimization models look through different scenarios to find the optimal layout design ) and labour management (Masoud et al 2018). In this work, we will discuss the irrigation monitoring aspect which will finalize this DDDAS framework.…”

Section: Methodsmentioning

confidence: 99%

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Data Driven Worker Routing for Irrigation Monitoring

Masoud,

Son

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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Survival and thrift in a globally competitive market strongly depend on the improvement of production quality while monitoring the pricing for grafting nurseries. Real-time monitoring of irrigation quality is a necessary yet cumbersome task for propagation facilities. Even for indoor facilities with automatic irrigation systems, this task remains bothersome due to the large greenhouses. The main goal of this paper is to propose an irrigation monitoring system to increase production productivity by minimizing the time workers spend on responding to irrigation monitoring calls. Here, a two-stage data-driven approach is proposed, where the traveling salesman model is implied on a reduced spatiotemporal network provided by Bayesian analysis to optimize workers routing for irrigation monitoring. The proposed approach is the final piece of a dynamic data-driven simulation-based optimization framework. The results over synthetic data demonstrate a potential reduction of 11.60% in traveled distance per worker per call.

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Section: Methodsmentioning

confidence: 99%

“…The simulated data includes the location of workers within the facility and the water consumption of the plants. The simulation models used in the DDDAS framework has been validated in these works (Masoud et al 2018;.…”

Section: Data Collectionmentioning

confidence: 99%

Data Driven Worker Routing for Irrigation Monitoring

Masoud,

Son

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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“…While, Shakibayifar et al 58 applied SBO technique to rescheduling train traffic in uncertain conditions during disruptions. Masoud et al 59 demonstrated the applicability of SBO in agriculture (horticultural nurseries).…”

Section: Literature Reviewmentioning

confidence: 99%

A complex garment assembly line balancing using simulation‐based optimization

Bongomin

Mwasiagi

Nganyi

et al. 2020

Engineering Reports

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The nascent wave of disruptive competition in the current business environment brought about by the fourth industrial revolution (Fashion 4.0 or Apparel 4.0) is enormous. Therefore, it is important for the apparel industry to be flexible enough to respond quickly to the unstable customers' demand through continuous improvement of their process efficiency and productivity. This study proposed assembly line balancing problem (ALBP) for complex garment assembly line using simulation-based optimization under stochastic task times. The proposed ALBP solution approach aimed at minimizing the cycle time for a given number of workstations with consideration of constraints on number of resources, precedence relations, and resource types. The empirical study was conducted at Southern Range Nyanza Limited (NYTIL) garment facility and a complex trouser assembly line with 69 workstations was considered. The discrete event simulation of the trouser assembly line was developed using Arena simulation software. The local optimal solution was obtained from simulation experiments which was adopted for the optimization process. The OptQuest tool was used to solve a single objective optimization with discrete control values. The results showed that the average throughput increased by 30% for local optimal line balancing and 55% for global optimal line balancing. Consequently, the cycle time reduced by 23% and 36%, respectively.

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