Multi-objective optimisation in scientific workflow

A Adapting Scientific Workflow Structures Using Multi-Objective Optimisation Strategies

Scientific workflows have become the primary mechanism for conducting analyses on distributed computing infrastructures such as grids and clouds. In recent years, the focus of optimisation within scientific workflows has primarily been on computational tasks and workflow makespan. However, as workflow-based analysis becomes ever more data intensive, data optimisation is becoming a prime concern...

Multi-objective Binary Search Optimisation

Preferences in Evolutionary Multi-Objective Optimisation

Multi-objective optimisation (MOO) is an important class of problem in engineering. The conflict of objectives in MOO places the issue of compromise in a central position. Since no single solution optimises all objectives, decision-making based on human preference is a part in solving MOO problems. In this paper application of the evolutionary MOO to the dynamic system controller design by use ...

Multi-objective and Scalable Heuristic Algorithm for Workflow Task Scheduling in Utility Grids

 To use services transparently in a distributed environment, the Utility Grids develop a cyber-infrastructure. The parameters of the Quality of Service such as the allocation-cost and makespan have to be dealt with in order to schedule workflow application tasks in the Utility Grids. Optimization of both target parameters above is a challenge in a distributed environment and may conflict one an...

Multi-objective particle swarm optimisation methods

This study compares a number of selection regimes for the choosing of global best (gbest) and personal best (pbest) for swarm members in multi-objective particle swarm optimisation (MOPSO). Two distinct gbest selection techniques are shown to exist in the literature, those that do not restrict the selection of archive members and those with ‘distance’ based gbest selection techniques. Theoretic...