Questions tagged [meta-heuristics]
For questions related to meta-heuristics (e.g. simulated annealing, tabu search, ant colony optimization algorithms, etc).
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What to do when Iterated Local Search (ILS) method keeps making the solution worse?
I've been trying to solve an optimization problem with ITERATED LOCAL SEARCH (ILS) method. I've generated the initial solution, then followed the steps of ILS. However, even after running the ...
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1answer
298 views
What is the difference between Stochastic Hill Climbing and Simulated Annealing?
I am reading about local search: hill climbing, and its types, and simulated annealing
One of the hill climbing versions is "stochastic hill climbing", which has the following definition:
...
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What is the difference between exploitation and exploration in the context of optimization?
In the paper Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm (2015, published in Knowledge-Based Systems)
The test functions are divided to three groups: unimodal, multi-...
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31 views
How are the lower and upper bound values of the moths determined in the Moth-Flame Optimization algorithm?
I am currently implementing the Moth-Flame Optimization (MFO) Algorithm, based on the paper: Moth-Flame Optimization Algorithm: A Novel Nature-inspired Heuristic Paradigm.
To calculate the values of ...
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1answer
39 views
What are most commons methods to measure improvement rate in a meta-heuristic?
When I run a meta-heuristics, like a Genetic Algorithm or a Simulated Annealing, I want to have a termination criterion that stops the algorithms when there is not any significant fitness improvement.
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Why does Simulated Annealing not take worse solution if the energy difference becomes higher?
In Simulated Annealing, a worse solution is accepted with this probability:
$$p=e^{-\frac{E(y)-E(x)}{kT}}.$$
If that understanding is correct: Why is this probability function used? This means that, ...
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0answers
23 views
Which of these two strategies is the best to select solutions in simulated annealing?
I am using simulated annealing (SA) for an NP-hard combinatorial optimisation problem.
1) I am testing over a range of problem instances in which the objective values can be in the 100's or in the ...
2
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1answer
105 views
What are advantages of using meta-heuristic algorithms on optimization problems?
What are the advantages and disadvantages of using meta-heuristic algorithms on optimization problems? Simply, why do we use meta-heuristic algorithms, like PSO, over traditional mathematical ...
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1answer
8k views
What is an objective function?
Local search algorithms are useful for solving pure optimization problems, in which the aim is to find the best state according to an objective
function.
My question is what is the objective function?
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1answer
129 views
Why can't I reproduce the experiments in the original paper that introduced the Firefly Algorithm?
I have been trying to reproduce the experiments done in the original: Firefly Algorithm for multimodal optimization (2010) by Xin-She Yang, but so far unsuccessfully. For the moment being, I'm okay if ...
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94 views
How to find proper parameter settings for a given optimization algorithm?
Is there any methodology to find proper parameter settings for a given meta-heuristic algorithm, e.g. the firefly algorithm or the cuckoo search? Is this an open issue in optimization? Is extensive ...
