Hmm..., sorry if the title sounds too geeky, but trust me, that is how things are here around me! This is also an inspiration drawn from my algorithms class and i thank my teacher for his unstoppable thoughts. I was pondering on how algorithms are applied and just thought of applying to our lives, and guess what? It works :)

Lets apply the concepts to a day to day activity like...waiting for a bus (actually, i am missing it a lot). Lets start with a liner programming model. Here your linear goal is to get into a bus that takes you to a desired destination and you are happy. The bounds of this equation become the bus being there on time and no traffic jams on the streets. This is how the problem is viewed in the discrete world. In the continuous world, you also have a range of values on the bus's state like it coming on time, being empty, you getting a window seat, your fellow passenger being sweet etc. etc....And along with this is the traffic constraints being continuous with values that the jam is small, manageable or a deadlock! (Bangaloreans need no intro to all these).

Now this continuous linear programming model can be given to a NP Solver to obtain a feasible solution and you might get something like getting up early and being in the bus stop before its too late, adjusting/sharing a seat with someone/ standing on the bus/ avoiding a crowded road (that depends on the bus driver's intelligence) etc etc.......... I too was expecting any of these but...........Oops! It says "NP Hard! Cannot solve any further!"

Yeah, many many activities are NP Hard. Just realised it and gave up thinking! Non convex optimization is something i need to master :)

Well, food for thought!

Disclaimer: I really dont know if the above concepts are mathematically right, but thats what i could make out in my class :( I also dont know if a NP Solver recognises a NP Hard problem. Need some light on them!