Introduction to Two-Stage Stochastic Optimization (Conceptual)

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Introduction to Two-Stage Stochastic Optimization (Conceptual)

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When the uncertainty in your decision-making process can be captured well by thinking of two stages (today and "tomorrow" or the near future) where "tomorrow" can be split into a number of different scenarios, two-stage stochastic optimization can be a useful modeling tool. For example: a farmer wants to decide what seeds to plant today considering the upcoming weather could be dry, average, or rainy. In this video, we go over the key concepts necessary to understand this type of optimization problem in preparation for an actual business example in the following video:
Concrete Excel example: • Two-Stage Stochastic O... .

Пікірлер: 29

@shu-boyang4941 3 жыл бұрын

The schematic picture for illustrating the idea of two-stage stochastic optimization is awesome. It makes everything so intuitive. Thank you for this great video.

@TallysYunes 3 жыл бұрын

Happy to hear it was helpful. Thank you for the feedback!

@zinebelqabli3101 2 жыл бұрын

@@TallysYunes dear professor, thank you for your effort, you have explained very well stochastic programming, I want to know if you have other videos on : - stochastic dynamic programming - Non-linear programming - Multi-objective programming - Fuzzy programming - Quadratic programming - linear/integer/mixed linear programming - Robust optimization - Dynamic programming

@giangdang3004 3 жыл бұрын

This video actually helps me understand my assignment. Thank you for a very informative video.

@TallysYunes 3 жыл бұрын

Great to hear! You're welcome!

@ahmedtawfiq3625 3 жыл бұрын

Some of the best contents i have found from your channel 👏🏽👏🏽

@TallysYunes 3 жыл бұрын

Thank you!

@imadeddineaziez7585 3 жыл бұрын

Very helpful, thank you very much !

@amirbaghban3068 2 жыл бұрын

Thank you for your clear teaching way ...

@qusayhamad7243 3 жыл бұрын

thank you

@hullopes 3 жыл бұрын

That was a really good class. Awesome! Tks!!

@TallysYunes 3 жыл бұрын

You're welcome! Glad you liked it!

@zinebelqabli3101 2 жыл бұрын

@@TallysYunes please sir, give me a concrete example of the application of this type of modeling approach in production planning, thank you

@zinebelqabli3101 2 жыл бұрын

dear professor, thank you for your effort, you have explained very well stochastic programming, I want to know if you have other videos on : - stochastic dynamic programming - Non-linear programming - Multi-objective programming - Fuzzy programming - Quadratic programming - linear/integer/mixed linear programming - Robust optimization - Dynamic programming

@zinebelqabli3101 2 жыл бұрын

@Tallys Yunes

@TallysYunes 2 жыл бұрын

I have only one video about stochastic DP. It's on the famous secretary problem: kzfaq.info/get/bejne/Z9WGipCHmJ7dmqM.html. If you look through my Excel Models playlist, there are several videos on linear/integer programming. The other topics (non-linear and multiobjective) are on my to-do list for upcoming videos.

@zinebelqabli3101 2 жыл бұрын

@@TallysYunes thank you , and what is the difference between SDP( stochastic dynamic programming) and DP( dynamic programming) ?

@TallysYunes 2 жыл бұрын

Stochastic DP takes into account the probabilities of each of the possible outcomes (new states) after you take an action in the current state. In deterministic (or, non-stochastic) DP there are no probabilities involved. So, for example, you can use standard DP to compute the optimal solution to an integer knapsack problem.

@zinebelqabli3101 2 жыл бұрын

@@TallysYunes Are "stochastic programming" and "stochastic dynamic programming" the same or is there a difference between these two approaches?

@tomdapchai 9 ай бұрын

thanks prof

@prashantpant8501 3 жыл бұрын

Hi professor, I have a small question. Say for example I have to prepare operation schedule for 2 machines- how much they should produce ( I have considered that there is no first stage variable the units are already commited=2). There is uncertainity of supply and demand, making in total S*D (scenarios). The problem is solved and we have one objective value, the solution for the production variable is different for S*D scenarios, but I need to provide one schedule for tomorrow. How to finalize one production schedule for tomorrow considering all the solutions from different scenarios?

@TallysYunes 3 жыл бұрын

What you describe doesn't sound right. The whole point of this type of stochastic optimization is that you must commit to making a decision *BEFORE* you know what will happen. You only know what can happen and the chances/likelihoods of each happening. Therefore, there must be stage-1 variables (today's decisions), or else the situation doesn't fit into a two-stage problem. In the production case, it must be that you need to commit to something today (maybe the schedule, i.e. how many units to make on each machine?). Perhaps there are additional details in your problem that you did not explain yet.

@joelmorley5 Жыл бұрын

In this generalised example, where does the stochasticity appear?

@TallysYunes Жыл бұрын

I'm guessing you're referring to the generalized example in the picture at timestamp 8:13. The stochasticity is in the fact that I'm not sure what my tomorrow will look like (it could be one of three possible things) and I have to make a decision today before the actual tomorrow gets revealed to me.