Re: How big a problem can ConstrainedMax handle?
- To: mathgroup at smc.vnet.net
- Subject: [mg31426] Re: How big a problem can ConstrainedMax handle?
- From: "Borut L" <borut at email.si>
- Date: Sat, 3 Nov 2001 18:25:03 -0500 (EST)
- References: <9rodc2$psp$1@smc.vnet.net> <9rqvjm$jis$1@smc.vnet.net> <9s0h7g$n66$1@smc.vnet.net>
- Sender: owner-wri-mathgroup at wolfram.com
"David Eppstein" <eppstein at ics.uci.edu> wrote in message news:9s0h7g$n66$1 at smc.vnet.net... > In article <9rqvjm$jis$1 at smc.vnet.net>, "Borut L" <borut at email.si> wrote: > > > My experience is that the ConstrainedMax is very handy and stylish, not > > having to type in the constraints in a conventional tableau form. The > > problem is basically number crunching in my opinion, so I used SIMPLX > > (simplex) algorithm from Numerical Recipes, being very satisfied with its > > limitness and high speed. > > Ok, but I specifically want an exact rational result, so numerical routines > are no good unless they are reimplemented in exact rationals. > > Anyway, I've heard from the Mathematica folks that ConstrainedMax is a > primal simplex using a dense representation, so may not be optimal for my > problem (sparse and with many more constraints than variables). But in the > absense of better alternatives I'm likely to try it anyway. > -- > David Eppstein UC Irvine Dept. of Information & Computer Science > eppstein at ics.uci.edu http://www.ics.uci.edu/~eppstein/ I recommend Mathematica if you want a rational result. Simplex algorithm is the method of choice because finding an optimal feasible vector in linear programming is a tough problem and the simplex does it in an easy way. I think every LP implementation uses it. Hey, btw: I've seen an article about LP and simplex method in an old Mathematica Journal. It was well written and nicely visualized (simplex cell). You can find it through volume indices.