Task mapping and scheduling are two very difficult problems that must be addressed when a sequential program is transformed into a parallel program. Since these problems are NP-hard, compiler writers have opted to concentrate their efforts on optimizations that produce immediate gains in performance. As a result, current parallelizing compilers either use very simple methods to deal with task s...

This chapter deals with the application of evolutionary approaches and other metaheuristic techniques for generating tree decompositions. Tree decomposition is a concept introduced by Robertson and Seymour [34] and it is used to characterize the difficulty of constraint satisfaction and NP-hard problems that can be represented as a graph. Although in general no polynomial algorithms have been f...

Hard optimization problems that cannot be solved within reasonable time by standard, mathematical, deterministic methods are of great practical interest. Metaheuristics inspired by nature were recently successfully used for such problems. These metaheuristics are based on random Monte-Carlo search guided by simulation of some nature intelligence, especially evolution and swarm intelligence. One...

Several methods exist for breaking symmetry in constraint problems, but most potentially suffer from high memory requirements, high computational overhead, or both. We describe a new partial symmetry breaking method that can be applied to arbitrary variable/value symmetries. It models dominance detection as a nonstationary optimisation problem, and solves it by resource-bounded metaheuristic se...

This research is focused on solving problems in the area of software project management using metaheuristic search algorithmsand as such is research in the field of search based software engineering. The main aim of this research is to evaluate the performance of different metaheuristic search techniques in resource allocation and scheduling problemsthat would be typical of software development...