Nowadays computers are also used to solve incredibly complex problems. To solve these problems we have to develop some advanced
algorithms. Exact algorithms of such problems might need unacceptably huge time & space to discover the solutions. For making the solution-finding
algorithms acceptable approximation algorithms have been developed. These approximation algorithms use the heuristics and meta- heuristics functions
to find out the solutions. Heuristic algorithms use the special designed functions to find out solution space intelligently.
Meta-heuristics algorithms are the iterative generation process which guides a subordinate heuristic for exploring and exploiting the search space.
Learning strategies in meta-heuristics helps to find efficient near-optimal solutions. Meta-heuristic algorithms make the complex problems solvable in
acceptable time. This survey paper is trying to explain heuristic and Meta-heuristic techniques to solve the complex problems.
Sachin Desale,Akhtar Rasool,Sushil Andhale,Priti Rane."Heuristic and Meta-Heuristic Algorithms and Their Relevance to the Real World: A Survey". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.2, Issue 05,pp.296-304, May - 2015, URL :https://ijcert.org/ems/ijcert_papers/V2I55.pdf,
: Heuristics, Meta-heuristic, genetic algorithm(GA), tabu search(TS), simulated annealing(SA), Local search, Evolutionary Algorithms,
Migrating Birds Optimization(MBO), Particle Swarm optimization(PSO), Artificial bee colony algorithm(ABC), Cuckoo search algorithm(CSA), Firefly algorithm(FA) , Harmony search(HS), Bat search algorithm(BSA).
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