A GRASP approach for makespan minimization on parallel batch processing machines

Authors:
Purushothaman Damodaran;Mario C. Vélez-Gallego;Jairo Maya
Affiliations:
Department of Industrial and Systems Engineering, Northern Illinois University, DeKalb, USA 60115;Departamento de Ingeniería de Producción, Universidad EAFIT, Medellín, Colombia;Departamento de Ingeniería de Producción, Universidad EAFIT, Medellín, Colombia
Venue:
Journal of Intelligent Manufacturing
Year:
2011

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Abstract

In this paper we consider the problem of scheduling a set of identical batch processing machines arranged in parallel. A Greedy Randomized Adaptive Search Procedure (GRASP) approach is proposed to minimize the makespan under the assumption of non-zero job ready times, arbitrary job sizes and arbitrary processing times. Each machine can process simultaneously several jobs as a batch as long as the machine capacity is not violated. The batch processing time is equal to the largest processing time among those jobs in the batch. Similarly, the batch ready time is equal to the largest ready time among those jobs in the batch. The performance of the proposed GRASP approach was evaluated by comparing its results to a lower bound and heuristics published in the literature. Experimental study suggests that the solution obtained from the GRASP approach is superior compared to other heuristics.