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Maximizing the Percentage of On-Time Jobs with Sequence Dependent Deteriorating Process Times

Author

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  • Alex J. Ruiz-Torres

    (Facultad de Administración de Empresas, Universidad de Puerto Rico – Rio Piedras, San Juan, PR, USA)

  • Giuseppe Paletta

    (Dipartimento di Economia e Statistica, Universita` della Calabria, Cosenza, Italy)

  • Eduardo Perez-Roman

    (Ingram School of Engineering, Texas State University, San Marcos, TX, USA)

Abstract

The paper addresses the problem of maximizing the percentage of on-time jobs in a parallel machine environment with sequence dependent deterioration. The deterioration of each machine (and therefore of the job processing times) is a function of the sequence of jobs that have been processed by the machine. Two machine loading strategies are combined with a set of list scheduling algorithms to solve the identical and unrelated machine versions of the problem. The proposed solutions approaches are tested using a large set of problem instances that consider various levels of the number of jobs and machines, the due date tightness, and the deterioration effect. The results indicate that the approach based on loading considering all machines simultaneously and assigns jobs by due date is the most effective.

Suggested Citation

  • Alex J. Ruiz-Torres & Giuseppe Paletta & Eduardo Perez-Roman, 2015. "Maximizing the Percentage of On-Time Jobs with Sequence Dependent Deteriorating Process Times," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 6(3), pages 1-18, July.
    • Handle: RePEc:igg:joris0:v:6:y:2015:i:3:p:1-18
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    Cited by:

    1. P. Senthil Kumar, 2018. "Linear Programming Approach for Solving Balanced and Unbalanced Intuitionistic Fuzzy Transportation Problems," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 9(2), pages 73-100, April.

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