We answer in negative a question of Gál and Miltersen [3] about a combinatorial game arising in the study of timespace trade-offs for data structures.

This paper is an attempt to make the discussion of parallel genetic algorithms independent from hardware issues. There have been many parallel implementations of genetic algorithms, some of them on hardware that is not even available any more. Most of these implementations have also modified the structure of the genetic algorithm for matters of efficiency, and it has been reported that these mo...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

Genetic algorithms (GAs) are receiving increased attention in di cult search and optimization applications, however in solving larger and more di cult search problems, adequate solutions may not be found in an expected range of time. Consequently multiple e orts have been conducted to make GAs faster and implementing them in parallel is one of the most promising choices [4]. Parallel GAs may be...

Present day engineering optimization problems often impose large computational demands, resulting in long solution times even on a modern high-end processor. To obtain enhanced computational throughput and global search capability, we detail the coarse-grained parallelization of an increasingly popular global search method, the particle swarm optimization (PSO) algorithm. Parallel PSO performan...

In this study, we started to investigate how the Partitioned Global Address Space (PGAS) programming language X10 would suit the implementation of a Constraint-Based Local Search solver. We wanted to code in this language because we expect to gain from its ease of use and independence from specific parallel architectures. We present our implementation strategy, and quest for different sources o...

The main goal of this paper is to argue for an approach to optimization in syntax that is not global (as is standardly assumed), but local, in the sense that syntactic optimization procedures can affect only small portions of syntactic structure. Local optimization presupposes harmonic serialism (rather than harmonic parallelism), i.e., a derivational organization of grammar. In line with this,...

A fast computation of unbiased global illumination is still an unsolved problem, especially if multiple bounces of light and non-diffuse materials are included. The standard Monte Carlo methods are time-consuming, because many incoherent rays are shot into the scene, which is hard to parallelize. On the other hand, GPUs can make the most of their computing power if the problem can be broken dow...

Variable Neighborhood Search (VNS) is a recent and effective metaheuristic for solving combinatorial and global optimization problems. It is capable of escaping from the local optima by systematic changes of the neighborhood structures within the search. In this paper several parallelization strategies for VNS have been proposed and compared on the large instances of the p-median problem. ∗The ...

This paper presents an algorithm that solves the Ren­ dering Equation to any desired accuracy, and can be run in parallel on distributed memory or shared memory com­ puter systems with excellent scaling properties. It appears superior in both speed and physical correctness to recent published methods involving bidirectional ray tracing or hybrid treatments of diffuse and specular surfaces. Like...