Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/76474
Title: Solving Multi-objective Optimal Design and Maintenance for Systems Based on Calendar Times Using NSGA-II
Authors: Cacereño Ibáñez, Andrés 
Galván González, Blas José 
Greiner Sánchez, David Juan 
UNESCO Clasification: 120715 Fiabilidad de sistemas
120302 Lenguajes algorítmicos
120326 Simulación
120601 Construcción de algoritmos
531108 Niveles óptimos de producción
Keywords: Availability
Design
Evolutionary Multi-Objective Algorithms
Multi-Objective Optimization
NSGA-II, et al
Issue Date: 2021
Publisher: Springer 
Journal: Computational Methods in Applied Sciences 
Conference: 13th EUROGEN International Conference 2019 
Abstract: Due to technical progress and business competition, design alternatives and maintenance strategies have to be contemplated to optimize the performance of physical assets when new facilities are projected and built. That combined optimization (Design & Maintenance) is required by all industrial installations to develop their activity in an increasingly competitive environment. The Design and Maintenance combined optimization process is a complex problem which requires research and development. The objectives to optimize are Unavailability (due to production losses) and Maintenance Cost (due to overcharge when it is not optimal). The Design and Maintenance strategy for a technical system are optimized jointly by modifying its Functionability Profile, which is closely related to the system’s availability. The Functionability Profile is generated by applying Monte Carlo Simulation that allows characterizing the process’ randomness until the failure and to modify that Functionability Profile by the optimal Maintenance strategy. An application case is presented, where several configurations of the elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) are used to optimize the multi-objective problem, successfully finding non-dominated solutions with optimum performance for the simultaneous Design and Maintenance strategy combination.
URI: http://hdl.handle.net/10553/76474
ISBN: 978-3-030-57421-5
ISSN: 1871-3033
DOI: 10.1007/978-3-030-57422-2_16
Source: Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences / António Gaspar-Cunha, Jacques Periaux, Kyriakos C. Giannakoglou, Nicolas R. Gauger, Domenico Quagliarella, David Greiner (eds). Computational Methods in Applied Sciences [ISSN 1871-3033], v. 55, p. 245-259, (Enero 2021)
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