I am struggling to implement a program based on simulated annealing to solve the traveling salesman problem. All solutions I got are not satisfying and i have no clue how to improve my implementati...

I would like to use Simulated Annealing to find local minimum of single variable Polynomial function, within some predefined interval. I would also like to try and find Global minimum of Quadratic ...

I am using simulated annealing, as implemented in R's package GenSa (function GenSA), to search for values of input variables that result in "good values" (compared to some baseline) of a highly di...

When picking a neighbor should the algorithm's temperature be considered? So for example if the temperature is high when picking a neighbor should be permutation be made? Or does the temperature on...

I am trying to implement Stoachastic Hill Climbing in Java. I understand that this algorthim makes a new solution which is picked randomly and then accept the solution based on how bad/good it is. ...

I'm looking to implement the simulated annealing algorithm in Java to find an optimal route for the Travelling Salesman Problem, so far I have implemented brute force and am looking to modify that ...

I am trying to use the scipy.optimize package to optimize a discrete optimization problem (global optimization). Acc to the doc, simulated annealing implemented in scipy.optimize.anneal should be a...

The authors of "Numerical Recipes" give in Ch. 10 an implementation of the simulated annealing algorithm that combines the "classical" simulated annealing with the Nelder-Mead downhill simplex meth...

I'm using scipy.optimize.curve_fit, but I suspect it is converging to a local minimum and not the global minimum. I tried using simulated annealing in the following way: def fit(params): return...

I am currently working on a project (TSP) and am attempting to convert some simulated annealing pseudocode into Java. I have been successful in the past at converting pseudocode into Java code, how...

What are the relevant differences, in terms of performance and use cases, between simulated annealing (with bean search) and genetic algorithms? I know that SA can be thought as GA where the popul...

Based on this original idea, that many of you have probably seen before: http://rogeralsing.com/2008/12/07/genetic-programming-evolution-of-mona-lisa/ I wanted to try taking a different approach: ...

I am using simulated annealing to solve an NP-complete resource scheduling problem. For each candidate ordering of the tasks I compute several different costs (or energy values). Some examples are ...

I'm doing a Simulated Annealing algorithm to optimise a given allocation of students and projects. This is language-agnostic pseudocode from Wikipedia: s ← s0; e ← E(s) // Initial state, energy....

I am doing parallel programming with MPI on Beowulf cluster. We wrote parallel algorithm for simulated annealing. It works fine. We expect 15 time faster execution than with serial code. But we did...