MATEC Web Conf.
Volume 302, 201918th International Conference Diagnostics of Machines and Vehicles
|Number of page(s)||10|
|Section||Diagnostics of Various Technical Objects|
|Published online||29 November 2019|
- P. Czyżak, A. Jaszkiewicz, Pareto simulated annealing - A metaheuristic technique for multiple-objective combinatorial optimization (J. Multi-Criteria Decision Anal., 1998) [Google Scholar]
- F. Grabski, Semi-Markov processes: Applications in system reliability and maintenance. (Amsterdam, Elsevier, 2014) [Google Scholar]
- F. Grabski, Analiza ryzyka w decyzyjnych semi-markowskich modelach procesu eksploatacji. Risk analysis in decision-making semi-Markov models of operation process, (XXXVIII Zimowa Szkoła Niezawodności. 38th Winter Reliability School, Szczyrk, 2010) [Google Scholar]
- M. Hapke, A. Jaszkiewicz, R. Słowiński, Pareto simulated annealing for fuzzy multi- objective combinatorial optimization. (J. Heuristics, 2000). [Google Scholar]
- J. H. Holland, Adaptation in natural and artificial systems (Ann Arbor, University of Michigan Press, 1975) [Google Scholar]
- L. Knopik, K. Migawa, A. Wdzięczny, Profit optimization in operation systems. (Polish Maritime Research, 2016) [Google Scholar]
- A. Konak, D. W. Coit, A. E. Smith, Multi-objective optimization using genetic algorithms: A tutorial (Reliability Engineering and System Safety, Elsevier, 2006) [Google Scholar]
- V. G. Kulkarni, Modeling and analysis of stochastic systems (New York, Chapman & Hall, 1995) [Google Scholar]
- K. W. Lee, Stochastic models for random-request availability (IEEE Trans, Reliability, 2000) [Google Scholar]
- K. Migawa, L. Knopik, A. Sołtysiak, P. Kolber, The method of risk assessment in transport system (Engineering Mechanics, Czech Republic, 2017) [Google Scholar]
- K. Migawa, L. Knopik, S. Wawrzyniak, Application of genetic algorithm to control the availability of technical systems (Engineering Mechanics, Czech Republic, 2016) [Google Scholar]
- D. K. Nam, C. Park, Multiobjective simulated annealing: A comparative study to evolutionary algorithms (Int. J. Fuzzy Syst., 2000) [Google Scholar]
- J. D. Schaffer, Multiple objective optimization with vector evaluated genetic algorithms (In: Proceedings of the international conference on genetic algorithm and their applications, 1985) [Google Scholar]
- B. Suman, P. Kumar, A survey of simulated annealing as a tool for single and multiobjective optimization (Journal of the Operational Research Society. 2006) [Google Scholar]
- A. Suppapitnarm, K. A. Seffen, G. T. Parks, P. Clarkson, A simulated annealing algorithm for multiobjective optimization (Eng. Opt., 2000) [Google Scholar]
- M. Szubartowski, K. Migawa, A. Neubauer, L. Knopik, Method of determining optimal control strategy (58th International Conference of Machine Design Departments, ICMD, 2017) [Google Scholar]
- E. L. Ulungu, J. Teghaem, P. Fortemps, D. Tuyttens, MOSA method: A tool for solving multiobjective combinatorial decision problems. (J. Multi-Criteri Decision Anal., 1999) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.