A two-stage Ant Colony Optimization algorithm to minimize the makespan on unrelated parallel machines with sequence-dependent setup times

Authors:
Jean-Paul Arnaout;Ghaith Rabadi;Rami Musa
Affiliations:
Industrial and Mechanical Engineering Department, Lebanese American University, Byblos, Lebanon;Engineering Management and Systems Engineering Department, Old Dominion University, Norfolk, USA 23529;Supply Chain Solutions, Agility Logistics, Atlanta, USA
Venue:
Journal of Intelligent Manufacturing
Year:
2010

Citing 9
Cited 11

Heuristics for scheduling unrelated parallel machines

Computers and Operations Research
Exact and approximation algorithms for makespan minimization on unrelated parallel machines

Discrete Applied Mathematics
Scheduling independent tasks to reduce mean finishing time

Communications of the ACM
Computers and Intractability: A Guide to the Theory of NP-Completeness

Computers and Intractability: A Guide to the Theory of NP-Completeness
Scheduling unrelated parallel machines to minimize total weighted tardiness

Computers and Operations Research
Heuristic methods for the identical parallel machine flowtime problem with set-up times

Computers and Operations Research
Scheduling unrelated parallel machines with sequence-dependent setups

Computers and Operations Research
Exact algorithms for a scheduling problem with unrelated parallel machines and sequence and machine-dependent setup times

Computers and Operations Research
Heuristic algorithms for unrelated parallel machine scheduling with a common due date, release dates, and linear earliness and tardiness penalties

Mathematical and Computer Modelling: An International Journal

ACO for the Surgical Cases Assignment Problem

Journal of Medical Systems
Discover scheduling strategies with gene expression programming for dynamic flexible job shop scheduling problem

ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
A variable neighborhood descent heuristic for the problem of makespan minimisation on unrelated parallel machines with setup times

Journal of Intelligent Manufacturing
Ant colony algorithms for a two-agent scheduling with sum-of processing times-based learning and deteriorating considerations

Journal of Intelligent Manufacturing
A variable neighborhood search approach for planning and scheduling of jobs on unrelated parallel machines

Journal of Intelligent Manufacturing
Makespan minimization for scheduling unrelated parallel machines with setup times

Journal of Intelligent Manufacturing
Simulation-based conjoint ranking for optimal decision support process under aleatory uncertainty

Journal of Intelligent Manufacturing
Exact and approximate methods for parallel multiple-area spatial scheduling with release times

OR Spectrum
A GEP-based reactive scheduling policies constructing approach for dynamic flexible job shop scheduling problem with job release dates

Journal of Intelligent Manufacturing
A particle swarm optimization for a fuzzy multi-objective unrelated parallel machines scheduling problem

Applied Soft Computing
A two-stage Ant Colony optimization algorithm to minimize the makespan on unrelated parallel machines--part II: enhancements and experimentations

Journal of Intelligent Manufacturing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper addresses the non-preemptive unrelated parallel machine scheduling problem with machine-dependent and sequence-dependent setup times. All jobs are available at time zero, all times are deterministic, and the objective is to minimize the makespan. An Ant Colony Optimization (ACO) algorithm is introduced in this paper and is applied to this NP-hard problem; in particular, the proposed ACO tackles a special structure of the problem, where the ratio of the number of jobs to the number of machines is large (i.e., for a highly utilized set of machines). Its performance is evaluated by comparing its solutions to solutions obtained using Tabu Search and other existing heuristics for the same problem, namely the Partitioning Heuristic and Meta-RaPS. The results show that ACO outperformed the other algorithms.