For clear understanding, follow this thread https://www.researchgate.net/post/What_are_the_differences_between_heuristics_and_metaheuristics.
I am giving an example here. In Permutation Flow shop problems NEH algorithm is a heuristic approach (http://www.sciencedirect.com/science/article/pii/0305048383900889), which is problem oriented and Genetic algorithm (meta-heuristic) is a black box method (http://www.sciencedirect.com/science/article/pii/S0305048305000174).
Given the propensity for computer people to generate unnecessary terms (myself included)....
If you feel confident about your own current understanding of the term heuristics then suspect that meta-heuristics is more of the same....
Meta-heuristic is something like "heuristic of heuristic".
Both heuristic and meta-heuristic don't guarantee to find global optimum but they guarantee to give you ANY solution (in finite time).
I will try to explain meta-heuristic on a base of genetic algorithm. It's "meta" because you need heuristics like mutation, crossover, selection operations but it's not specified HOW to implement them.
Optimization algorithms can be roughly divided into two categories: exact algorithms and heuristics. Exact algorithms are designed in such a way that it is guaranteed that they will find the optimal solution in a finite amount of time. However, for very difficult optimization problems (e.g. NP-hard or global optimization) this "finite amount of time" may increase exponentially respect to the dimensions of the problem. Heuristics do not have this guarantee, and therefore generally return solutions that are worse than optimal. However, heuristic algorithms usually find "good" solutions in a "reasonable" amount of time.
Many heuristic algorithms are very specific and problem-dependent. On the other hand, a metaheuristic is a high-level problem-independent algorithmic frame-work that provides a set of guidelines or strategies to develop heuristic optimization algorithms. But a concrete definition has been elusive and in practice many researchers and practitioners interchange these terms. Thus, the term metaheuristic is also used to refer to a problem specific implementation of a heuristic optimization algorithm according to the guidelines expressed in such a framework.
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