Abstract
Metaheuristic algorithms have been an interesting and widely used area for scientists, researchers and academicians because of their specific and significant characteristics and capabilities in solving optimization problems. Metaheuristic algorithms are developed base on inspiration of some real world phenomenon in nature or on the behavior of living being (animal, insects, organic living beings). On the past many metaheuristic algorithms have been introduced and applied on various problems of various domains including real world optimization problems. This paper is aimed to provide a historical Survey on metaheuristic algorithms, it will provide a list of metaheuristic based algorithms ordered according to the foundation year, with the name of Authors and the algorithm abbreviations.Â
Highlights
The complexity of the real life problems are in increasing in a manner that it become Difficult for the traditional mathematical programming methods to solve and optimize them
In the past the methods that have a stochastic mechanisms often called heuristic algorithm, nowadays in the recent studies it refer to as metaheuristics which is a combination of two words Meta and Heuristic, were the world “heuristic” means finding or discovering a goal by trial and error, and the world “meta” means a beyond or higher level, that means a metaheuristics generally refers a “higher level of heuristics” [5]. generally metaheuristic algorithms represent as a "master strategy that guides and modifies other heuristics to produce solutions beyond those that are normally generated in a quest for local optimality" [6]
Local search metaheuristics refers to a group of methods which depend on a neighborhood, which are a set of candidate states, that are connected directly to the current state and can be reached by a single move for finding a best solution for computationally hard optimization problems
Summary
The complexity of the real life problems are in increasing in a manner that it become Difficult for the traditional mathematical programming methods to solve and optimize them. Most of the real-life optimizations problems are nonlinear, complex, multimodal, and they have a incompatible objectives functions in which the process of obtaining an optimal or even near-optimal solutions is a very difficult task, even for a single easy and linear objective functions, sometimes, an optimal solutions may not exists at all, generally, there is no guarantee of getting an optimal solution for real-life problems [1] [2]. Metaheuristics Optimization Algorithms become a very active area of researches and one of the most well known high-level procedure designed for generating, selecting or finding a heuristic that optimize solutions and provide a sufficiently better, improved and fittest solutions to a given objective functions for a real-life optimization problem [3] [4]. In this paper we will present a number of metaheuristics algorithm according to the year of its appearance
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