Static scheduling of a program represented by a directed task graph on a multiprocessor
system to minimize the program completion time is a well-known problem in parallel …

The increasing complexity of real-world optimization problems raises new challenges to
evolutionary computation. Responding to these challenges, distributed evolutionary …

Variable neighborhood search (VNS) is a metaheuristic for solving combinatorial and global
optimization problems whose basic idea is a systematic change of neighborhood both within …

A new model for task scheduling that dramatically improves the efficiency of parallel systems
Task scheduling for parallel systems can become a quagmire of heuristics, models, and …

To program in distributed computing environments such as grids and clouds, workflow is
adopted as an attractive paradigm for its powerful ability in expressing a wide range of …

The problem of scheduling a parallel program represented by a weighted directed acyclic
graph (DAG) to a set of homogeneous processors for minimizing the completion time of the …

We have developed a genetic algorithm (GA) approach to the problem of task scheduling for
multiprocessor systems. Our approach requires minimal problem specific information and no …

Future requirements for computing speed, system reliability, and cost-effectiveness entail the
development of alternative computers to replace the traditional von Neumann organization …

Industrial systems usually draw huge energy to run various machines. The amount of energy
requirement has again increased due to the automation of the industrial plants to make them …

High-performance clusters have been widely deployed to solve challenging and rigorous
scientific and engineering tasks. On one hand, high performance is certainly an important …