Minimizing the Total Completion Time and Total Earliness Time Functions for a Machine Scheduling Problem Using Local Search Methods
Machine Scheduling Problem
Multiple Objective Functions
Simulated Annealing
Particle Swarm Optimization
In this paper we investigate the use of two types of local search methods (LSM), the Simulated Annealing (SA) and Particle Swarm Optimization (PSO), to solve the problems ( ) and . The results of the two LSMs are compared with the Branch and Bound method and good heuristic methods. This work shows the good performance of SA and PSO compared with the exact and heuristic methods in terms of best solutions and CPU time.
