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Kanban Allocation Policies of Multi-product Production Control Strategies
Published in Khojasteh Yacob, Production Management, 2017
Oladipupo Olaitan, Paul Young, John Geraghty
Due to the effectiveness of this simulation-based optimization approach, some simulation software have inbuilt optimization blocks that are based on some of these algorithms. For example, ExtendSimTM, which is described in this chapter, uses a Genetic Algorithm to which an objective function and the parameters for optimization can be specified. The Genetic Algorithm (Hollandand Reitman 1977) has been expressed as a mechanism that imitates the genetic evolution of species (Pirlot 1996). It operates by reproduction, crossover, and mutation of populations; the population being the solution space to the specified problem (Sivakumar and Shahabudeen 2008). The reproduction operator selects an initial population of solutions, evaluates them for fitness, and ranks them. Individuals with good fitness are combined as parents to produce offspring, with the hope that the offspring will retain some of the desirable traits of the parents. The offspring then go through mutation and evaluation to see if they can evolve into even better individuals. In the context of optimizing pull strategies, an individual can be seen as a particular setting of kanbans and/or base-stocks for all the manufacturing stages, and its mutation would involve interchanging these settings.
Introduction
Published in Jon Steinar Gudmundsson, Flow Assurance Solids in Oil and Gas Production, 2017
Engineering and natural sciences are used to find answers to flow assurance solids challenges and problem. The results are often formulated and implemented in proprietary computer programs; commercial simulation software. The use of simulation software requires many skills and the running of sophisticated simulations does not guarantee correct results. The various theoretical assumptions underlying any and all software must be understood to ensure proper application. This holds equally true for flow assurance solids calculations. Engineers and scientists working on flow assurance solids projects need to be skilled in the fundamentals; they need to be skilled in the art of the field of study.
Advances in Simulation Studies for Developing Energy-Efficient Buildings
Published in Amritanshu Shukla, Atul Sharma, Sustainability through Energy-Efficient Buildings, 2018
Karunesh Kant, Amritanshu Shukla, Atul Sharma
Along with the development of materials and construction techniques, energy simulation software tools of buildings have also developed over the years. Currently, there are several energy simulation software tools with different levels of complexity and response to different variables. Among the available simulation software tools are the CFD, COMSOL Multiphysics, Fluent, Transient System Simulations (TRNSYS), Energy Plus, Open Studio®, RADIANCE, REQUEST, TRANE TRACE 700, SIMERGY, FORTRAN, and MATLAB.
Modeling and assessing earth-air heat exchanger using the parametric performance design method
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2022
Wei Yu, Xiaofei Chen, Qingsong Ma, Weijun Gao, Xindong Wei
Concluded from existing studies, tube, soil, and weather parameters are three major categories that can affect the performance of EAHE. Thus, it is important to apply EAHE in a real place for experiment and analysis by taking the three categories of parameters into account. It is also rare to see a comprehensive study that explores the effect of various parameters on EAHE performance in cold climate zone (a hot and humid summer and cold and windy winter) in China, and there are no studies that investigate EAHE performance in Qingdao. Furthermore, existing studies also show a lack of appropriate and convenient tools for evaluating the performance of EAHE due to the complexity of existing models and software. Mihalakakou et al (Mihalakakou et al. 2021). argues that the modeling and evaluation of the performance of EAHE usually require professional knowledge. Typically, engineers use computational fluid dynamics (CFD) simulation software (Ahmed et al. 2021; Mirzazade Akbarpoor, Haghighi Poshtiri, and Biglari 2021), EnergyPlus (Ascione et al. 2016; Darkwa et al. 2011), TRANSYS (Baglivo and Maria Congedo 2017; Long et al. 2022) and other software for analysis. However, it would be rather difficult for designers to accurately evaluate environmental and economic impacts and make decisions in the early stages.
Towards the EU emissions targets of 2050: optimal energy renovation measures of Finnish apartment buildings
Published in International Journal of Sustainable Energy, 2019
Janne Hirvonen, Juha Jokisalo, Juhani Heljo, Risto Kosonen
Decarbonisation of national energy systems is an important goal. Such plans have been studied before, such as in a German study which examined how 100% of German energy use could be covered by renewable energy (Henning and Palzer 2014). However, in that study, the improvements in the building sector were modelled in a simplified way, without taking into account any specific energy renovation measures. Conversely, in this study, the specifics of the building sector are examined in more detail, as a precursor for a later study on the whole national energy system. As it is not individual buildings, but the whole building stock that determines the importance of the performance improvements, it is imperative to know the age distribution of different types of buildings existing in a nation. This affects their structural and HVAC solutions, determining the energy performance of the building stock. When this is known, energy renovations can be prioritised according to the emission reduction potential available. There are different methods to find out the energy consumption of buildings. Probabilistic energy consumption models were studied in (Barkhudaryan, Roshan, and Orosa 2016). Increasingly common, however, is the use of dynamic building simulation software such as EnergyPlus, TRNSYS or IDA-ICE (Nageler et al. 2018). Typically, studies on optimal building designs and retrofitting have been done by calculating the performance of a set amount of pre-defined design packages, such as in (Ferreira et al. 2016). However, this limits the number of possible options and may not provide the truly optimal solution. It is becoming increasingly common to combine simulation software with optimisation algorithms to provide more accurate design information (Nguyen, Reiter, and Rigo 2014).
Group dynamics analysis and the correction of coal miners' unsafe behaviors
Published in Archives of Environmental & Occupational Health, 2021
Linlin Wang, Qinggui Cao, Chenggong Han, Jie Song, Nannan Qu
One of the characteristics of SD is the carrying out of simulations via special SD software. Commonly used simulation software includes Vensim, AnyLogic, iThink, STELLA and Powersim. Among them, Vensim is a simple and visual graphic interface software that is used to establish the relevant models, including the causal relationship and flow diagram, of all elements in a system. Based on the characteristics of Vensim and the simulation purposes, this software was chosen as the simulation tool in the present study.