An algorithm of simulated annealing for the job shop scheduling problem is presented. The proposed algorithm restarts with a new value every time the previous algorithm finishes. To begin the process of annealing, the starting point is a randomly generated schedule with the condition that the initial value of the makespan of the schedule does not surpass a previously established upper bound. The experimental results show the importance of using upper bounds in simulated annealing in order to more quickly approach good solutions.
CITATION STYLE
Cruz-Chavez, M. A., & Frausto-Solis, J. (2004). Simulated annealing with restart to job shop scheduling problem using upper bounds. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3070, pp. 860–865). Springer Verlag. https://doi.org/10.1007/978-3-540-24844-6_133
Mendeley helps you to discover research relevant for your work.