Production-ratio oriented optimization for multi-recipe material handling via simultaneous hoist scheduling and production line arrangement

Zhao, Chuanyu; Fu, Jie; Xu, Qiang

doi:10.1016/j.compchemeng.2012.10.016

Cited by 16 publications

(5 citation statements)

References 24 publications

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“…Although microfluidic integration with microinjection has allowed improved throughput, [ 84,92 ] dosage control, [ 83,93 ] automation, [ 91 ] and usability, [ 94 ] most are limited in system complexity, low scalability, reproducibility, and inconsistent delivery, and these should be addressed to enable wider usage and applications.…”

Section: Mechanical Plasma Membrane Disruption‐mediated Intracellular Delivery (Mechanoporation)mentioning

confidence: 99%

Microfluidic and Nanofluidic Intracellular Delivery

Hur

Chung

2021

Advanced Science

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Innate cell function can be artificially engineered and reprogrammed by introducing biomolecules, such as DNAs, RNAs, plasmid DNAs, proteins, or nanomaterials, into the cytosol or nucleus. This process of delivering exogenous cargos into living cells is referred to as intracellular delivery. For instance, clustered regularly interspaced short palindromic repeats (CRISPR)‐Cas9 gene editing begins with internalizing Cas9 protein and guide RNA into cells, and chimeric antigen receptor‐T (CAR‐T) cells are prepared by delivering CAR genes into T lymphocytes for cancer immunotherapies. To deliver external biomolecules into cells, tools, including viral vectors, and electroporation have been traditionally used; however, they are suboptimal for achieving high levels of intracellular delivery while preserving cell viability, phenotype, and function. Notably, as emerging solutions, microfluidic and nanofluidic approaches have shown remarkable potential for addressing this open challenge. This review provides an overview of recent advances in microfluidic and nanofluidic intracellular delivery strategies and discusses new opportunities and challenges for clinical applications. Furthermore, key considerations for future efforts to develop microfluidics‐ and nanofluidics‐enabled next‐generation intracellular delivery platforms are outlined.

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Section: Mechanical Plasma Membrane Disruption‐mediated Intracellular Delivery (Mechanoporation)mentioning

confidence: 99%

Microfluidic and Nanofluidic Intracellular Delivery

Hur

Chung

2021

Advanced Science

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“…Other mixed-integer linear programming model for multirecipe and multistage material handling processes is developed in Zhao et al [16]. In this research, the authors simultaneously consider the production line arrangement, and the customized production ratio.…”

Section: Related Workmentioning

confidence: 99%

Simulation Optimization for the Multihoist Scheduling Problem

Pérez-Rodríguez

2021

Applied Computational Intelligence and Soft Computing

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Although the Multihoist Scheduling Problem (MHSP) can be detailed as a job-shop configuration, the MHSP has additional constraints. Such constraints increase the difficulty and complexity of the schedule. Operation conditions in chemical processes are certainly different from other types of processes. Therefore, in order to model the real-world environment on a chemical production process, a simulation model is built and it emulates the feasibility requirements of such a production system. The results of the model, i.e., the makespan and the workload of the most loaded tank, are necessary for providing insights about which schedule on the shop floor should be implemented. A new biobjective optimization method is proposed, and it uses the results mentioned above in order to build new scenarios for the MHSP and to solve the aforementioned conflicting objectives. Various numerical experiments are shown to illustrate the performance of this new experimental technique, i.e., the simulation optimization approach. Based on the results, the proposed scheme tackles the inconvenience of the metaheuristics, i.e., lack of diversity of the solutions and poor ability of exploitation. In addition, the optimization approach is able to identify the best solutions by a distance-based ranking model and the solutions located in the first Pareto-front layer contributes to improve the search process of the aforementioned scheme, against other algorithms used in the comparison.

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“…The design dimension, however, was rarely tackled associated to the scheduling one. It was sometimes linked to the production line arrangement where the aim was to optimize the spatial allocation of the processing resources, like in Zhao et al [52]. Qu et al [42], yet, studied the simultaneous design and operation problem of CHSP but in 2-Dimension case.…”

Section: The Chsp With Other Optimization Objectivesmentioning

confidence: 99%