Deterring the optimum design of large-scale structures is a difficult task. Great number of design variables, largeness of the search space and controlling great number of design constraints are major preventive factors in performing optimum design of large-scale truss structures in a reasonable time. Meta-heuristic algorithms are known as one of the useful tools to d...

Meta-heuristics are methods that sit on top of local search algorithms. They perform the function of avoiding or escaping a local optimum and/or premature convergence. The aim of this paper is to survey, compare and contrast meta-heuristics for local search. First, we present the technique of local search (or hill climbing as it is sometimes known). We then present a table displaying the attrib...

Meta-programming is a well-known technique widely used in logic programming and artificial intelligence. Meta-interpreters are powerful tools especially for writing expert systems in general and for writing their inference machines in particular. While the traditional approach to meta-interpretation is based on the syntactic definition of a meta-interpreter, new approach presented in this paper...

Although over a thousand scientific papers address the topic of load forecasting every year, only a few are dedicated to finding a general framework for load forecasting that improves the performance, without depending on the unique characteristics of a certain task such as geographical location. Meta-learning, a powerful approach for algorithm selection has so far been demonstrated only on uni...

Quadratic assignment problem (QAP) is a well-known problem in the facility location and layout. It belongs to the NP-complete class. There are many heuristic and meta-heuristic methods, which are presented for QAP in the literature. In this paper, we applied 2-opt, greedy 2-opt, 3-opt, greedy 3-opt, and VNZ as heuristic methods and tabu search (TS), simulated annealing, and particle swarm optim...

In this paper one of the new generation soft computing technique that is known as Gene Expression Programming (GEP) is used to develop a meta-model for the multiobjective design of a hypothetical production line. The developed meta-model is used to optimize production line design with Multiple Objective Tabu Search algorithm (MOTS). It is found out that GEP and MOTS can be effectively used to s...