An integrated prognostic based hybrid genetic-immune algorithm for scheduling jobs and predictive maintenance

Ladj, Asma; Tayeb, Fatima Benbouzid-Si; Varnier, Christophe

doi:10.1109/cec.2016.7744045

Cited by 11 publications

(14 citation statements)

References 5 publications

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“…The choice of this heuristic method is justified by its adaptability regarding the individuals and operators definitions as well as its performances to reach a good solution in a satisfying computation time. The genetic algorithm principle is based on the hybrid genetic-immune algorithm proposed by Ladj et al (2016). The operators are adapted to be applied in a random deterioration case as Ladj et al (2016) develop it for a deterministic deterioration case.…”

Section: A Genetic Algorithm Based Methodsmentioning

confidence: 99%

“…The genetic algorithm principle is based on the hybrid genetic-immune algorithm proposed by Ladj et al (2016). The operators are adapted to be applied in a random deterioration case as Ladj et al (2016) develop it for a deterministic deterioration case. Its general main principle is illustrated in Figure 3.…”

Section: A Genetic Algorithm Based Methodsmentioning

confidence: 99%

“…The total population includes the parents and their children with their possible mutations and contains 2N pop individuals. As explained by Ladj et al (2016), diversification and intensification are two major issues when building effective search algorithms. Diversification refers to the capacity to explore different regions of the search space while intensification refers to the ability to generate high fitted solutions in those regions.…”

Section: A Genetic Algorithm Based Methodsmentioning

confidence: 99%

“…A balance between these two notions has to be obtained. When the iteration number n i is a multiple of the iteration period i p , the population dispersion is estimated through the coefficient of variation (CV), also known as the Relative Standard Deviation (RSD) (Ladj et al (2016)). CV considers the fitness value of each schedule π i in the total population P op (Eq.9).…”

Section: A Genetic Algorithm Based Methodsmentioning

confidence: 99%

“…Feng et al (2016) apply a genetic algorithm to minimize the costs induced by jobs tardiness, corrective and preventive maintenance action. Ladj et al (2016) suggest an approach hybridizing genetic algorithms and artificial immune systems. A deterministic deterioration model is considered as each job deteriorates the machine of a fixed value and it is assumed that no accidental failure occurs during the time horizon.…”

Section: Introductionmentioning

confidence: 99%

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A predictive approach to jointly schedule missions and maintenances for a deteriorating vehicle

Robert¹,

Bérenguer²,

Bouvard³

et al. 2018

Safety and Reliability – Safe Societies in a Changing World

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Both for the manufacturer and the user of industrial vehicles, optimizing simultaneously the maintenance and missions schedule at the fleet level becomes a necessity to improve the profitability. Lots of researches have been realized to optimize either the preventive maintenance schedule or the production planning. Integrating both activities in the same schedule has become a new hotspot. Few researches have been led to schedule both maintenance operations and missions for a fleet of systems which deteriorate over time in a comprehensive predictive approach. As a first step to reach this objective, a single vehicle is considered and we propose a method to jointly optimize its predictive maintenance and its mission planning using the remaining useful life and deterioration information. The vehicle has a set of missions to complete. The aim is to group the missions in blocks and interpose maintenance operations between these blocks. However, the vehicle deteriorates over time and each mission impacts differently the deterioration according to its severity. A stochastic process is used to model the deterioration phenomenon and its parameters are changed for each mission. To obtain the best arrangement between missions and maintenance operations, a genetic algorithm is used. A criterion to minimize the maintenance cost is defined, which takes into account preventive and corrective maintenance costs associated with the missions failure probabilities. The genetic algorithm enables to approach the optimal solution in a reasonable time and avoid considering every possible arrangement.

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Section: A Genetic Algorithm Based Methodsmentioning

confidence: 99%

Section: A Genetic Algorithm Based Methodsmentioning

confidence: 99%

Section: A Genetic Algorithm Based Methodsmentioning

confidence: 99%

Section: A Genetic Algorithm Based Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations