Optimization of problems which are restricted by non-linear constraints is often difficult. Evolutionary algorithms, in particular, are found to deteriorate significantly in performance on problems ...

Genetic Algorithm (GA) - with multiple choices of Selection ... (with multiple local minima), and is used as a performance-test problem for optimization algorithms. It is a typical example of ...

We use optimization for finding the best solution to any problem. Optimization using genetic algorithms can be considered genetic optimization, and there are several benefits of performing ...

A genetic algorithm is a prime example of technology imitating nature to solve complex problems, in this case, by adopting the concept of natural selection in an evolutionary algorithm. Genetic ...

The TSP is a NP-hard problem in optimization studied in both operations research and computer science. Metaheuristics are efficient alternative techniques for NP-hard and greater dimensional problems ...

Osyczka, A. and Kundu, S. (1995) A New Method to Solve Generalized Multicriteria Optimization Problems Using the Simple Genetic Algorithm. Structural Optimization, 10, 94-99. has been cited by the ...

Developments were made to the basic Tabu Search to adapt it to the optimisation problem. This paper explains the contribution ...