Consideration of processing time dissimilarity in batch-cyclic scheduling of flowshop cells

Almasarwah, Najat; Süer, Gürsel A.

doi:10.1080/00207543.2020.1818863

Cited by 6 publications

(1 citation statement)

References 52 publications

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“…In PMS, a group of similar machines is grouped in a certain area to serve one or more of several objectives such as minimizing the total tardiness, number of tardy jobs, maximum tardiness, and flow time (YounesSinaki, et al, 2022). Various methods including metaheuristic, mathematical model, heuristic algorithms and others were proposed in the literature to schedule (n) jobs into (m) identical parallel machines given different objectives such as minimization of the total tardiness, number of tardy jobs, or maximum tardiness and makespan (Almasarwah & Süer, 2021;Kim & Kim 2021;Verma et al, 2021). One effective method for tackling identical PMS is mathematical modeling.…”

Section: Introductionmentioning

confidence: 99%

An Accurate and Robust Genetic Algorithm to Minimize the Total Tardiness in Parallel Machine Scheduling Problems

RAMADAN,

ALMASARWAH,

ABDELALL

et al. 2023

Management and Production Engineering Review

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This paper uses a Genetic Algorithm (GA) to reduce total tardiness in an identical parallel machine scheduling problem. The proposed GA is a crossover-free (vegetative reproduction) GA but used for four types of mutations (Two Genes Exchange mutation, Number of Jobs mutation, Flip Ends mutation, and Flip Middle mutation) to make the required balance between the exploration and exploitation functions of the crossover and mutation operators. The results showed that use of these strategies positively affects the accuracy and robustness of the proposed GA in minimizing the total tardiness. The results of the proposed GA are compared to the mathematical model in terms of the time required to tackle the proposed problem. The findings illustrate the ability of the propounded GA to acquire the results in a short time compared to the mathematical model. On the other hand, increasing the number of machines degraded the performance of the proposed GA.

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