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 so many combinatorial optimization problems, Job shop scheduling problems have earned a reputation for being difficult to solve. Genetic algorithm has demonstrated considerable success in providing efficient solutions to many non-polynomial-hard optimization problems. In the field of job shop scheduling, genetic algorithm has been intensively researched, but it's converge speed is not favorable...
This paper deals with the Job Shop Scheduling Problem (JSP) with the objective of minimizing the makespan criterion, the time elapsed between the start of the first job and end of the last job arranged in a job sequence. We propose a novel multi-population based framework called HADP-JSP to solve the JSP. In the HADP-JSP the main population is divided into several groups. Each group adaptively chooses...
The Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing, and Tabu search that belong to the Evolutionary Computations Algorithms (ECs) are not suitable for fine tuning structures as they neglect all conventional heuristics. In most of the NP-hard problems, the best solution rarely be completely random, it follows one or more rules (heuristics). In this paper a new algorithm...
A new hybrid optimization algorithm is proposed for the problem of finding the minimum makespan in the job-shop scheduling environment. The new algorithm is based on the principle of particle swarm optimization (PSO). PSO employs a collaborative population-based search, which combines local search (by self experience) and global search (by neighboring experience), possessing high search efficiency...
We propose a new and efficient hybrid heuristic scheme for solving job-shop scheduling problems (JSP). A new and efficient population initialization and local search concept, based on genetic algorithms, is introduced to search the solution space and to determine the global minimum solution to the JSP problem. Simulated results imply that the proposed novel JSP method (called the PLGA algorithm) outperforms...
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.