Efficient Parallelization and Performance Analysis of Meta-heuristics on Many-core Platforms

Abstract

Meta-heuristics are an efficient method for solving complex problems in science, engineering, and industry. They explore the solution space efficiently to generate a good solution in a reasonable time through a neighborhood or population-based local search. Even if the meta-heuristics do it efficiently, for large instances (practical problems of science, engineering, or industry), generation of neighborhood and evaluation of solution of single-solution based meta-heuristics or population-based meta-heuristics takes a tremendous amount of time.