Student competition

Three categories

  • Minimization

  • Nonlinear systems

  • Least Squares problems

Objective of the competition:

  1. Solve the maximum number of problems

  2. Minimize the cost of the solution

Competition timetable:

  • Competition begin at 9.00 on February 20, 2012

  • 10 problems for each category are proposed to the competitors

  • Student must write a matlab function which solve each problem

  • Function must have signature like: function x=MySolution(x0,fun) where x(:,i) is the i-th iterate, x0 the starting point and fun the function to be minimize

  • Competition end at 21.00 on March 2, 2012

  • End of the competition is postponed at 24.00 on March 18, 2012

Competition ranking formation

  • Each competitor gets a point for each problem his program is able to solve

  • “undisclosed” problem (for each category) are use in rank formation

  • The winner is the competitor which maximize points (maximize number of problems solved)

  • In case of equal score with 2 or more competitor a computational cost index is used:

  1. For each problem an additional point is attributed to competitor that minimizes the index: nf + n * ng + n^2 * nh where nf number of function evaluation, ng number of gradient evaluation, nh number of hessian evaluation.

  2. In case of nonlinear system the index is: nF + n * nJ where nF number of map evaluation, nJ number of jacobian evaluation.

  • In case equal score (very unlikely) additional and more difficult problems are considered until a winner is found

Computational limitation for each problem

  • n is the number of unknowns

  • A limit of 1000 iteration

  • A limit of n*n*1000 function evaluations

  • A limit of n*1000 gradient evaluations

  • A limit of 1000 hessian evaluations

  • Competition opened!

text of competition (UPDATED)