metaheuristic

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metaheuristic

(algorithm, complexity, computability)
A top-level general strategy which guides other heuristics to search for feasible solutions in domains where the task is hard.

Metaheuristics have been most generally applied to problems classified as NP-Hard or NP-Complete by the theory of computational complexity. However, metaheuristics would also be applied to other combinatorial optimisation problems for which it is known that a polynomial-time solution exists but is not practical.

Examples of metaheuristics are Tabu Search, simulated annealing, genetic algorithms and memetic algorithms.
This article is provided by FOLDOC - Free Online Dictionary of Computing (foldoc.org)
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To solve this problem, a Meta heuristic algorithm, MOAMP, has been used (based on tabu search).
Lots of heuristic algorithm [5-23] and meta heuristic algorithm [24, 25] have been proposed to solve the problem by an approximate optimal solution.
Meta Heuristic Optimization Methods for Under Voltage Load Shedding Scheme by Raja Masood Larik and M Wazir Mustafa of University Teknologi, Malaysia, Skudai Johor Bahru and NED University.
In this part try to optimize an object function with Meta heuristic algorithms like PSO and HS.
The major advantage of using a Meta heuristic algorithm is that it performs optimization.
From the implementation of taboo search meta heuristic to solve the TSP routing problem of picking the coffee at the trading company in southwestern Antioquia, it is clear that this offers the greatest efficiency more than PLPC strategy (Farther position closer position) of routing, because the distance is reduced by 44% (16.5m) as well as time and cost of preparation of orders for pick up packages of coffee required by customers.
A greedy algorithm is a meta heuristic algorithm when it makes decisions for each step based on what seems best at the current step.
For proving efficiency of the Meta heuristic algorithm, solution of the algorithm is compared with solution of GAMS software.
Guidelines For The Use Of Meta Heuristics In Combinatorial Optimization // European Journal of Operation Research, 2004.--No.
Interest in meta-heuristics has generated the development of hybrid approaches [8] and recent significant advances have combined meta heuristics with other problem solving paradigms and improved their use in important application areas [23].
One reason is that many developers are afraid of dealing with complex multiple vehicle routing algorithms as this requires in depth experience with meta heuristics, which is of course not the primary focus of modern software engineers," Vincent Mayer says, (DNA's responsible engineer for application integration).
Topics include linear, nonlinear, queuing, decision analysis, meta heuristics, robust optimization, and large-scale networks.