Author(s)

Crescenzio Gallo, Vito Capozzi

Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy.

An algorithm using the heuristic technique of Simulated Annealing to solve a scheduling problem is presented, focusing on the scheduling issues. The approximated method is examined together with its key parameters (freezing, tempering, cooling, number of contours to be explored), and the choices made in identifying these parameters are illustrated to generate a good algorithm that efficiently solves the scheduling problem.

Scheduling, Simulated Annealing, Discrete Optimization Algorithm

Gallo, C. and Capozzi, V. (2019) A Simulated Annealing Algorithm for Scheduling Problems. Journal of Applied Mathematics and Physics, 7, 2579-2594. doi: 10.4236/jamp.2019.711176.