An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects

Touafek, Nesrine; Tayeb, Fatima Benbouzid-Si; Ladj, Asma; Dahamni, Alaeddine; Baghdadi, Riyadh

doi:10.1007/978-3-031-16014-1_51

Cited by 1 publication

(6 citation statements)

References 29 publications

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“…Although the ABC metaheuristic of [54] gave better solutions than the VNS algorithm, which is considered an efficient metaheuristic for the problem [83,84], the IQABC algorithm outperforms it, as can clearly be seen from Table 1 for the two maintenance modes. This is proved by the employed bees' local search procedures and the QL-driven neighborhood selection.…”

Section: Performance Analysis Of Iqabc Algorithm Without Learning And...mentioning

confidence: 92%

“…Finally, considering the case of combined effects, Ref. [54] proposed an ABC algorithm to solve the joint flowshop scheduling problem under the timedependent deteriorating effect and position-dependent learning effect. Ref.…”

Section: Metaheuristic Solution Approachmentioning

confidence: 99%

“…Furthermore, variable maintenance durations due to learning or deteriorating effects is also an important research stream in the scheduling literature. While variable maintenance durations due to the deterioration effect have most often been considered [56][57][58], variable maintenance durations due to the learning effect have scarcely been studied [54,59].…”

Section: Metaheuristic Solution Approachmentioning

confidence: 99%

“…To prove the performance of the integrated QL-driven ABC algorithm without learning and deterioration effects (IQABC), we compared it with three different competing algorithms for the same problem and constraints without considering the learning and deteriorating effects. The comparative algorithms are : (1) a population-based metaheuristic, which is the ABC algorithm of [54] with random neighborhood selection; (2) a unique solution-based metaheuristic, which is the Variable Neighbor Search (VNS) algorithm of [83]; (3) and finally, INEH, our newly designed constructive heuristic. The comparison was carried out by means of 1100 runs of the test benchmark.…”

Section: Performance Analysis Of Iqabc Algorithm Without Learning And...mentioning

confidence: 99%

“…The execution results are compared with the ABC learning algorithm (ABC-LE) reported in [54]. Indeed, the IQABC-LE algorithm implements a QL mechanism to guide the neighbor structure selection in the employed bees phase, instead of random selection as in ABC-LE.…”

Section: Performance Analysis Of the Ql-driven Abc Algorithm With Lea...mentioning

confidence: 99%

See 4 more Smart Citations

A Reinforcing-Learning-Driven Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance under Learning and Deteriorating Effects

Touafek,

Benbouzid-Si Tayeb,

Ladj

2023

Algorithms

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In the last decades, the availability constraint as well as learning and deteriorating effects were introduced into the production scheduling theory to simulate real-world case studies and to overcome the limitation of the classical models. To the best of our knowledge, this paper is the first in the literature to address the permutation flowshop scheduling problem (PFSP) with flexible maintenance under learning and deterioration effects to minimize the makespan. Firstly, we address the PFSP with flexible maintenance and learning effects. Then, the deteriorating effect is also considered. Adaptive artificial bee colony algorithms (ABC) enhanced with Q-learning are proposed, in which the Nawaz–Enscore–Ham (NEH) heuristic and modified NEH heuristics are hybridized with a maintenance insertion heuristic to construct potential integrated initial solutions. Furthermore, a Q-learning (QL)-based neighborhood selection is applied in the employed bees phase to improve the quality of the search space solutions. Computational experiments performed on Taillard’s well-known benchmarks, augmented with both prognostic and health management (PHM) and maintenance data, demonstrate the effectiveness of the proposed QL-driven ABC algorithms.

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Section: Performance Analysis Of Iqabc Algorithm Without Learning And...mentioning

confidence: 92%

Section: Metaheuristic Solution Approachmentioning

confidence: 99%

Section: Metaheuristic Solution Approachmentioning

confidence: 99%

Section: Performance Analysis Of Iqabc Algorithm Without Learning And...mentioning

confidence: 99%

Section: Performance Analysis Of the Ql-driven Abc Algorithm With Lea...mentioning

confidence: 99%

See 3 more Smart Citations

A Reinforcing-Learning-Driven Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance under Learning and Deteriorating Effects

Touafek,

Benbouzid-Si Tayeb,

Ladj

2023

Algorithms

Self Cite

View full text Add to dashboard Cite

show abstract

An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects

Cited by 1 publication

References 29 publications

A Reinforcing-Learning-Driven Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance under Learning and Deteriorating Effects

A Reinforcing-Learning-Driven Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance under Learning and Deteriorating Effects

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