14 votes
Accepted

Linear optimization problem with user-defined cost function

First, the problem is not a linear optimization problem, at least not for the objective function shown (which is nonlinear due the conditional portion in lines 10-13 and particularly the division by ...
prubin's user avatar
  • 38.8k
11 votes
Accepted

Search approach to solve optimization problem with only a minimum where time series get scaled

Your problem actually comes down to a constrained linear regression problem where $z$ is your dependent variable, the $x_j$ for $j=1,\dots,n$ are your independent variables and $s$ is your vector with ...
Rolf van Lieshout's user avatar
10 votes
Accepted

Black-box optimization with linear programming?

My experience in this may be a bit dated (it comes from a previous millennium), but back then I recall (vaguely) using a form of response surface methodology to optimize parameters in a simulation ...
prubin's user avatar
  • 38.8k
9 votes

Search approach to solve optimization problem with only a minimum where time series get scaled

The bounty convinced me to compete with Rolf's excellent answer, which is exactly how I would approach the problem myself. Next to CPLEX and Gurobi, it also worth noting that MATLAB and Octave provide ...
Kevin Dalmeijer's user avatar
8 votes

Black-box optimization with linear programming?

AFAIK, it depends on the optimization problem under study. As @Kuifje said, black boxes are used when the problem is too complex. One of the ways to apply simulation-optimization is to use discrete ...
A.Omidi's user avatar
  • 8,642
8 votes
Accepted

In Local Search, which reheating techniques have a good track record?

This is where automatic algorithm configuration and design comes to the rescue. In my experience, different combinations of strategies work equally fine, at least when combined with other components ...
Alberto Franzin's user avatar
7 votes

Difference between exploration and exploitation in Simulated Annealing algorithm

I personally see it as follows. In simulated annealing the likelihood of choosing a solution from the neighborhood is quite high at the beginning. This phase could be regarded as exploration as the ...
PeterBe's user avatar
  • 1,632
6 votes
Accepted

Terrain Ruggedness Index for optimization problem

Yes. The ruggedness of a landscape is a measure of how much variability is observed between neighbouring solutions, and it can be computed using the landscape correlation function. Rugged landscapes (...
Alberto Franzin's user avatar
6 votes

Difference between exploration and exploitation in Simulated Annealing algorithm

Those two are also called Diversification (Exploration) and Intensification (Exploitation). In SA, Diversification relates to the larger values of the probability of accepting an inferior neighbor ...
Mostafa's user avatar
  • 2,104
6 votes

Linear optimization problem with user-defined cost function

If you want to implement an algorithm on your own, then we suggest a randomized, derivative-free search, even simpler than a Nelder-Mead approach. Given a feasible solution (respecting the sum equal ...
Hexaly's user avatar
  • 2,966
5 votes

How to solve knapsack problem with simulated annealing?

Simulated annealing is just a (meta)heuristic strategy to help local search to better escape local optima. Local search for combinatorial optimization is conceptually simple: move from a solution to ...
Hexaly's user avatar
  • 2,966
2 votes

Objective function for employee assignation problem solved with simulated annealing

I think that there is not enough information to create a optimization problem in this case. If you have more (or the same number of) employees than the needed to execute the task, all the employees ...
nilson mendes's user avatar

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