A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines

Abstract

Abstract. Industrial planning has experienced notable advancements since its beginning by the middle of the 20th century. The importance of its application within the several industries where it is used has been demonstrated, regardless of the difficulty of the design of the exact algorithms that solve the variants. Heuristic methods have been applied for planning problems due to their high complexity; especially Artificial Intelligence when developing new strategies to solve one of the most important variants called task scheduling. It is possible to define task scheduling as: .a set of N production line tasks and M machines, which can execute those tasks, where the goal is to find an execution order that minimizes th» accumulated execution time, known as makespan. This paper presents a GRASP meta heuristic strategy for the problem of scheduling dependent tasks in different machines

GRASP algorithm for the unrelated parallel machine scheduling problem with setup times and additional resources

“…Laguna and Velarde (1991) solve the just-in-time scheduling problem in parallel machines and they propose an approach that combines elements of GRASP algorithm and Tabu Search. Finally, some other fields in which GRASP algorithms have been successfully applied are project scheduling (see Alvarez-Valdes et al (2008)), cutting and packing (see Parreño et al (2010)), and industrial applications (see Anticona (2006)).…”

Out‐of‐core Data Management for Path Tracing on Hybrid Resources

“…Scheduling Arguably the most performance‐critical and complex component of our system is the scheduling of tasks. Path tracing is a Monte Carlo algorithm, which disqualifies scheduling techniques that require predictable tasks [Ant06, CDM97, Nos98], however, recent work has investigated scheduling less predictable tasks. Boyer and Hura schedule dependent tasks by using a random ordering technique combined with re‐evaluation of estimated task execution times [BH04].…”