Genetic Algorithms

Pelikán, Martin

doi:10.1002/9780470400531.eorms0357

Cited by 3 publications

(2 citation statements)

References 40 publications

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“…The concept of MSaaS has been discussed extensively in the literature. We refer the interested reader to key publications (Cayirci 2013;MSG-131 2015;Hannay, Berg, et 21 See Pelikan (2011) for an excellent introduction. Shahin, Babar, and Chauhan 2020;Kratzke and Siegfried 2020) and focus this section on previous work within the Modelica community.…”

Section: Related Workmentioning

confidence: 99%

A Cloud-native Implementation of the Simulation as a Service-Concept Based on FMI

Stüber¹,

Frey²

2021

Linköping Electronic Conference Proceedings

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Providing modelling and simulation capabilities as a service promises to increase their value by improving accessibility for non-expert users and software agents as well as by leveraging cloud-computing technology to scale simulation performance beyond the capabilities of a single computer. In order to reach this potential, implementations must align their design with the architectural styles of cloud computing applications and the web in general.We present an open-source, cloud-native Simulation as a Service (SIMaaS)-implementation that gives access to models and allows simulating them on the web. The implementation uses Functional Mockup Units (FMUs) for co-simulation as an executable form of a model and relies on FMPy for simulation. It is realized as a microservice in the form of a REST-based HTTP-API. Functionality and performance are demonstrated by using the service to create ensemble forecasts for PV systems and to search for an optimal parameter set using a genetic algorithm. Conceptual limitations and the resulting opportunities for further work are summarized.

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Section: Related Workmentioning

confidence: 99%

A Cloud-native Implementation of the Simulation as a Service-Concept Based on FMI

Stüber¹,

Frey²

2021

Linköping Electronic Conference Proceedings

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“…The new populations are not randomly generated because the chromosomes that are part of the current population are selected, mixed, and modified through genetic operators, such as selection, crossing, and mutation, to generate new chromosome sequences [31]. The new population, known as offspring, incorporates only the fittest chromosomes into the offspring, inhibiting the chromosomes that are less suitable.…”

mentioning

confidence: 99%

Meta-Heuristic Model for Optimization of Production Layouts Based on Occupational Risk Assessment: Application to the Portuguese Wine Sector

Freitas

Lima

Gaspar

2022

ASI

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A factory layout is a decisive factor in the improvement of production levels, efficiency, and even in the sustainability of a company. Regardless of the type of layout to be implemented, they are typically designed to optimize the work conditions and provide high performance, reducing production losses. The wine sector encompasses a wide diversity of possible configurations of production layouts, from one-level designs with separate infrastructures in several buildings or centralized single facilities, or even subdivided into different levels or floors. The general purpose is to maximize energy efficiency and process performance while minimizing costs. Thus, an optimization model based on the organization of productive layouts is proposed, using a methodology based on a genetic algorithm. The obtained results reveal that the optimization model for winery layouts was successfully applied, providing feasible solutions to improve the production processes’ efficiency combined with the minimization of general and ergonomic risks.

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Bayesian hierarchical multi-objective optimization for vehicle parking route discovery

Beed

Sarkar

Roy

2020

Innovations Syst Softw Eng

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Discovering an optimal route to the most feasible parking lot has been a matter of concern for any driver which aggravates further during peak hours of the day and at congested places leading to considerable wastage of time and fuel. This paper proposes a Bayesian hierarchical technique for obtaining the most optimal route to a parking lot. The route selection is based on conflicting objectives and hence the problem belongs to the domain of multi-objective optimization. A probabilistic data driven method has been used to overcome the inherent problem of weight selection in the popular weighted sum technique. The weights of these conflicting objectives have been refined using a Bayesian hierarchical model based on Multinomial and Dirichlet prior. Genetic algorithm has been used to obtain optimal solutions. Simulated data has been used to obtain routes which are in close agreement with real life situations.

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Genetic Algorithms

Cited by 3 publications

References 40 publications

A Cloud-native Implementation of the Simulation as a Service-Concept Based on FMI

A Cloud-native Implementation of the Simulation as a Service-Concept Based on FMI

Meta-Heuristic Model for Optimization of Production Layouts Based on Occupational Risk Assessment: Application to the Portuguese Wine Sector

Bayesian hierarchical multi-objective optimization for vehicle parking route discovery

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