Meta-heuristics have already received considerable attention in various fields of engineering optimization problems. Each of them employes some key features best suited for a specific class of problems due to its type of search space and constraints. The present work develops a Pseudo-random Directional Search, PDS, for adaptive combination of such heuristic operators. It utilizes a short term...

fuzzy cognitive maps (fcms) have successfully been applied in numerous domains to show the relations between essential components in complex systems. in this paper, a novel learning method is proposed to construct fcms based on historical data and by using meta-heuristic: genetic algorithm (ga), simulated annealing (sa), and tabu search (ts). implementation of the proposed method has demonstrat...

Local search, in either best or first admissible form, generally suffers from poor solution qualities as search cannot be continued beyond locally optimal points. Even multiple start local search strategies can suffer this problem. Meta-heuristic search algorithms, such as simulated annealing and tabu search, implement often computationally expensive optimisation strategies in which local searc...

Quadratic Assignment Problem (QAP) is an NPhard combinatorial optimization problem, therefore, solving the QAP requires applying one or more of the meta-heuristic algorithms. This paper presents a comparative study between Meta-heuristic algorithms: Genetic Algorithm, Tabu Search, and Simulated annealing for solving a real-life (QAP) and analyze their performance in terms of both runtime effici...

Exact optimization algorithms are not able to provide an appropriate solution in solving optimization problems with a high-dimensional search space. In these problems, the search space grows exponentially with the problem size therefore; exhaustive search is not practical. Also, classical approximate optimization methods like greedy-based algorithms make several assumptions to solve the problem...

In this research application paper, the usefulness of an intelligent mechanism (a cubic spline smoothing technique) for determining when to switch from one algorithm to another within a meta heuristic search process is explored. We concentrated on a typical planning problem for a southern United States forestry company where the net present value of management activities is maximized subject to...

We present a state-of-the-art survey of parallel meta-heuristic developments and results, discuss general design and implementation principles that apply to most meta-heuristic classes, instantiate these principles for the three meta-heuristic classes currently most extensively used—genetic methods, simulated annealing, and tabu search, and identify a number of trends and promising research dir...