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Let us discuss about the advantages, disadvantages, and use of powerful decomposition techniques like Bender's decomposition for large-scale optimization. I invite my esteemed colleagues and researchers to share important literature, ways of implementation, and potential application areas of decomposition algorithms, in this forum.
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Dear R.K
You are right, we can't say no, because we don't know about new developments.
Probably, one of the reasons by which Bender's decomposition technique has not been applied to MCDM - and I share your opinion about its application - is because problems in MCDM are systems, and like that, they can't be partitioned, other than for study.
Your last paragraph resumes the same point, better than my sketchy explanation, so, we agree
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When we are dealing with Large-Scale Global Optimization (LSGO), what is the best-based approach: algorithms-based decomposition or algorithms-based Non decomposition?
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Mathematical programming is the best optimization tool with many years of strong theoretical background. Also, it is demonstrated that it can solve complex optimization problems on the scale of one million design variables, efficiently. Also, the methods are so reliable! Besides, there is mathematical proof for the existence of the solution and the globality of the optimum.
However, in some cases in which there are discontinuities in the objective function, there would be some problems due to non-differentiable problem. Some methods such as sub-gradients are proposed to solve such problems. However, I cannot find many papers in the state-of-the-art of engineering optimization of discontinuous optimization using mathematical programming. Engineers mostly use metaheuristics for such cases.
Can all problems with discontinuities be solved with mathematical programming? Is it easy to implement sub-gradients for large scale industrial problems? Do they work in non-convex problems?
A simple simple example of such a function is attached here.
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Your ideas for dividing the region and using local optimizer are so nice!
Thanks a lot!
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Hello, I am interested in tracking the decrease in initiation events of different wildland fuel combustion.
Apart from the experimental procedures, is there any simulation software that can help me model the suppression of a burning object through water or water mixed with chemical additives?
Thank you in advance.
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I have mostly worked on accessing the combustion of coal and its causes through various sensors. However, CFD (computational fluid dynamics) have sufficient space for tracking the status of the fire.
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Can anyone please suggest appropriate scales for measuring university graduates' voluntary and involuntary unemployment, subjective and objective employability and visible and invisible underemployment? 
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Very helpful..thanks a lot, you both! 
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Hello everyone,
Recent studies show that 70-90% of construction Megaprojects suffer cost and time overrun due to poor risk management, this underlines that the existing risk management and uncertainty management fail to manage these projects effectively. In your point of view, what is the main limitations and weaknesses associated with existing standard uncertainty management approaches in Megaprojects context?
Thank you in advance for your comments,
Mustafa
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Dear Dharmesh K. Oza.
Could you please clarify further how the weaknesses that you have mentioned above are related to the poor performance of uncertainty management? As I see some of them are just a normal risk by itself such as "Fluctuation in labour, supervisor , project manager and construction manager"
Regards,
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I am searching for FSM algorithms (with exact or approximate search) that perform for General Graphs Input . Thank you 
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You can check out two below papers. Hope it helps.
1. G-Tries: a data structure for storing and finding subgraphs
2. LC-mine: a framework for frequent subgraph mining with local consistency techniques
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I would like to screen any approaches in which researchers modelled energy efficiency in energy system models (ESM) since I am interested to integrated the feature of energy efficiency into an equilibrium model with multiple fuels. Energy efficiency measures may take place on the demand side as well as on the supply side.
Thanks a lot for any hints concerning this issue!
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Hi Andreas,
I'm not aware of any review of the role of energy efficiency in ESMs, but I would be very interested to read one. I suspect that the reason a review is not apparent is that ESMs are not ideal at modelling energy efficiency, generally being cost-optimisation models, which would usually chose energy efficiency improvements where individuals or companies would not chose, because of the "energy efficiency gap" and so forth. Uptake of energy efficiency in these models is often disincentivised by adding hurdle rates.
Curious if you find any good literature. 
Best,
Hannah
(I work with UK TIMES and TIAM-UCL)
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Given an auto-scaling system, we face inputs that have unpredictable patterns and volumes. Because they are allocated per input resource, fluctuations of input volume have much overhead of the resource. Can you identify an algorithm that can help the systems performance?
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Another manifestation of this same problem might be in local management of a non-stationary random process - if we have a sequence of sensor measurements (for example), limited to 16-bit words (say), then we want to scale the range to maximize the precision (this can be a linear or logarithmic map, depending on the sensor) - it seems like this question is about algorithms to track the extreme values of such a time series to stay as close as possible to the maximum precision - this is a matter of adjusting the data model (the definition of how the bits are to be interpreted) to fit the local empirical behavior of the time series - is this a reasonable interpretation of the original question?