One of the 12 labors of Hercules, according to ancient lore, was to destroy a nine-headed monster called the Hydra. The challenge was that when Hercules used his sword to chop off one of the monster's heads, two would grow back in its place. He therefore needed an additional weapon, a torch, to vanquish his foe. There are parallels between this legend and our three-years-and-counting battle with SARS-Cov-2, the virus that causes Covid-19. Every time scientists have thought they'd subdued one strain of the virus -- be it alpha, beta, delta, or omicron -- another variant or subvariant emerged a short while later.

Since MIP linear problems include both continuous and integer variables, they are proved to belong to the NP-hard class (see [38] for a more detailed analysis), meaning that they are not solvable in polynomial time. The complete exploration of the integer feasible set, whose cardinality grows exponentially with the number of variables, is yet possible to achieve the optimal solution, but for most of the practically significant instances, it would require unacceptable computational effort. In fact, the only way to solve to optimality any mixed-integer problem is to apply some of the well-known Branch and Bound techniques. However, despite combinatorial optimization community provided a great deal of these algorithms, for which the reader should refer to [31, 34, 16], MIP problems complexity is inherent with their belonging to NP-hard class. Therefore, when tackling MIP problems, one either seeks particular structures allowing to bring down the complexity, such as the availability, for a given class of problems, of the optimal formulation or exploits cutting plane generation to dramatically reduce the feasible region dimension. However, we often encounter MIP problems without having any prior knowledge of possible structures and, thus, pursuing the globally optimal solution could be in practice impossible or inefficient, since for our purpose a sub-optimal approximation is considered to be good enough. This makes heuristics one of the most widespread and feasible ways to achieve sub-optimal solutions of MIP problems within an affordable computational time. For the purpose of highlighting the perspective of our research, we can define two classes of MIP heuristics: improvement heuristics and start heuristics.

'The Five' panel weighs in on Disney's protest over the new Florida law. This is a rush transcript of "The Five" on March 30, 2022. This copy may not be in its final form and may be updated. It's five o'clock in New York City, and this is THE FIVE. WATTERS: Yet another big American company going woke. Disney caving to the liberal mob and pledging to help repeal the new parental rights bill that just signed into law by Florida Governor Ron DeSantis. Which Democrats and the media have completely lied about and called them bigoted? RON DESANTIS (R-FL): For a company like Disney to say that the bill should have never passed, first of all, Tucker, they weren't saying anything when this is going through the House. They only started doing this because the mob, the woke mob came after them. But put that aside, for them to say that them as a California-based company are going to work to take those California values and overturned a law that was duly enacted, and as you said, supported by a strong majority of Floridians, they don't run the state. We have done a bill that prohibited talking about the abuse of Uyghurs in China, Disney would support that legislation. Now they know it's hello, everyone, or hello friends. When we brought the fireworks back to the magic kingdom, we no longer say ladies and gentlemen, boys and girls, we say dreamers of all ages. PIERS MORGAN, FOX NEWS CO-HOST: By the way, sorry, but when you can't even say ladies and gentlemen anymore or boys and girls. What in the world is happening in the world? WATTERS: Would you like to go ahead. I was going to ask Greg. WATTERS: Piers, with your, you know, very, very rude habits. GUTFELD: I think I just had a stroke. MORGAN: You deserve a pretty outburst of rage. My heart -- (CROSSTALK) MORGAN: Honestly, it is so pathetic, isn't it? You can't go to a theme park and you can't hear the word ladies and gentlemen, boys and girls.

Otter CEO and Silicon Valley-based serial entrepreneur Sam Liang created a cloud-based artificial intelligence engine to power its automated speech to text transcription service. In my 25-plus-year career--and counting!--as a journalist, I've done thousands of interviews and attended even more meetings, either face to face or over the phone which, for lots of them, I had to manually transcribe the conversations to make sure that I got my interlocutors' comments right--a chore that I dreaded. So when my friend Marie Domingo introduced me to Otter.ai at the TechCrunch Disrupt conference in San Francisco last fall--she was handling their public relations at that time--I was, of course, curious to know more about how this mobile app works but highly skeptical that it would actually help me. After more than six months using the free version of the service that includes 600 minutes of free transcriptions per month, Otter.ai Not only does the app (for iOS and Android) do an excellent job in transcribing my live interviews and meetings from speech to text with great accuracy--and letting me focus on the actual conversations rather than taking notes verbatim--but it made the notes totally searchable which is an amazing time saver when I'm looking for specific keywords.