Hi,

I would like to use ALGENCAN to optimize many problems of the

following type

minimize 1/2 * X' A X - c X

subject to b<= X <= 1

Sum_i x_i = 1

Also, the matrix A is diagonal but could have negative entries. So I

have a quadratic programming problem with only one linear equality

constraint and upper/lower bounds. In my case X is large. (could have

at most 100k entries)

I had two questions

1. I don't know much about optimization so I was reading around for a

simple polynomial time algorithm to solve my problem exactly. I found

a O(n) time algorithm but the restriction is that matrix A should have

entries > 0. Does anyone know of an algorithm for the general case

where the diagonal elements in A can be any real number.

2. If there isn't a solution to 1, I'd like to use ALGENACN for my

problem. I'm trying it out right now and after reading some of the

messages in the group, I'm using the following options in my

algencan.dat file

TRUNCATED-NEWTON-LINE-SEARCH-INNER-SOL

TRUE-HESSIAN-PRODUCT-IN-CG

ADD-SLACKS

FEASIBILITY-TOLERANCE 1.0d-03

OPTIMALITY-TOLERANCE 1.0d-03

I've compiled ALGENCAN with ma57 as well. Should I be using other

options ? I have to otimize thousands of optimizations of the

aforementioned type so running time is important here.I kept the

tolerances high because I didn't want a very accurate solution at the

expense of time. Is that the right way to go ? Any suggestions are

welcome.

Thanks!

Ashish