The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In typical production scheduling problems, flow shop scheduling is one of the strongly NP-complete combinatorial optimisation problems with a strong engineering background. In this paper, after investigating the effect of different initialisation, crossover and mutation operators on the performances of a genetic algorithm (GA), we propose an effective hybrid heuristic for flow shop scheduling. First,...
As a class of typical production scheduling problems, job shop scheduling is one of the strongly NP-complete combinatorial optimisation problems, for which an enhanced genetic algorithm is proposed in this paper. An effective crossover operation for operation-based representation is used to guarantee the feasibility of the solutions, which are decoded into active schedules during the search process...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.