A meta-heuristic with self-adjusting parameters for the unrelated parallel machine problem

Munoz F.T.; Baesler F.F.; Moraga R.J.

Keywords: optimization, setting, logic, algorithms, scheduling, parallel, parameter, machine, meta-raps, heuristic, processes, problems, problem, programming, solving, Random

Abstract

This paper presents an application of Meta-RaPS (Meta-heuristic for Randomized Priority Search) to the unrelated parallel machine scheduling problem with sequence-and-machine dependent setup times, where the objective is to minimize the makespan (Rm|Sijk|Cmax)- Meta-RaPS constructs and improves feasible solutions at each iteration through the utilization of randomized rules. After a number of iterations the best solution is kept. In this application, Meta-RaPS uses a self-adjusting mechanism to update its parameters as the search goes on. This mechanism is based on the gradient search method and explores the two-parameter space systematically until the best setting is found. The mechanism used as well as Meta-RaPS application is explained in detail, tested, and compared with results from literature.

Más información

Título de la Revista: 1604-2004: SUPERNOVAE AS COSMOLOGICAL LIGHTHOUSES
Editorial: ASTRONOMICAL SOC PACIFIC
Fecha de publicación: 2006
URL: http://www.scopus.com/inward/record.url?eid=2-s2.0-36448936744&partnerID=q2rCbXpz