Title: Maximising the number of on-time jobs on parallel servers with sequence dependent deteriorating processing times and periodic maintenance

Authors: Eduardo Pérez; Rahul R. Ambati; Alex J. Ruiz-Torres

Addresses: Ingram School of Engineering, Texas State University, 601 University Drive San Marcos, TX 78666, USA ' Department of Computer Science, Texas State University, 601 University Drive San Marcos, TX 78666, USA ' Facultad de Administración de Empresas, Universidad de Puerto Rico – Rio Piedras, San Juan, PR 00931-3332, USA

Abstract: This paper considers a parallel-machine scheduling problem with sequence dependent processing times and periodic maintenance. The time to complete jobs increases as the machines deteriorate and the machine deterioration depends on the particular job sequence assigned to a machine. The planned maintenance activity returns the machine to its optimal condition, and all machines undergo this maintenance activity at the same time. The objective is to find the job schedule that maximises the number of on-time jobs given a specified maintenance schedule. The paper presents a mathematical programming formulation, several solution algorithms, and evaluates their performance under various experimental conditions.

Keywords: parallel machines; machine deterioration; late jobs; on-time jobs; scheduling; maintenance.

DOI: 10.1504/IJOR.2018.092735

International Journal of Operational Research, 2018 Vol.32 No.3, pp.267 - 289

Received: 24 Oct 2014
Accepted: 06 Aug 2015
Published online: 29 Jun 2018 *

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