A Hybrid Algorithm Based on PSO and ACO Approach for Solving Combinatorial Fuzzy Unrelated Parallel Machine Scheduling Problem
Flexible and agile manufacturing systems have led to the growing interest in scheduling problems considering both earliness and tardiness penalties. The problem studied in this paper is the Unrelated Parallel machine Earliness-Tardiness Non-common Due Date Sequence-dependent set-up time scheduling Problem (UPETNDDSP) for jobs with varying processing times, where the objective is to minimize the sum of the absolute deviations of job completion times from their corresponding due dates for the different weighted earliness and tardiness combinations. A hybrid approach based on Particle Swarm Optimization algorithm (PSO) and Ant Colony Optimization algorithms (ACO) have been devised to generate optimal solutions for different weighted earliness and tardiness measures. Fuzzy logic approach is been used to select the optimal weighted earliness-tardiness combinations in an unrelated parallel machine environment.