Scheduling rules to minimize total tardiness in a parallel machine problem with setup and calendar constraints

Authors:
Jacques Lamothe;Francois Marmier;Matthieu Dupuy;Paul Gaborit;Lionel Dupont
Affiliations:
Université Toulouse, Mines Albi, Centre Génie Industriel, Campus Jarlard-Route de Teillet, 81013 Albi CT Cedex 09, France;Université Toulouse, Mines Albi, Centre Génie Industriel, Campus Jarlard-Route de Teillet, 81013 Albi CT Cedex 09, France;Pierre Fabre Médicament Production, Parc Industriel de la Chartreuse, 81106 Castres Cedex, France and Université Toulouse, Mines Albi, Centre Génie Industriel, Campus Jarlard-Route ...;Université Toulouse, Mines Albi, Centre Génie Industriel, Campus Jarlard-Route de Teillet, 81013 Albi CT Cedex 09, France;Université Toulouse, Mines Albi, Centre Génie Industriel, Campus Jarlard-Route de Teillet, 81013 Albi CT Cedex 09, France
Venue:
Computers and Operations Research
Year:
2012

Citing 10
Cited 2

Priority rules for job shops with weighted tardiness costs

Management Science
Minimizing total tardiness on one machine is NP-hard

Mathematics of Operations Research
Scheduling jobs on parallel machines applying neural network and heuristic rules

Computers and Industrial Engineering
Dynamic programming algorithms for scheduling parallel machines with family setup times

Computers and Operations Research
Scheduling Algorithms

Scheduling Algorithms
An Agent-Based Approach for Scheduling Multiple Machines

Applied Intelligence
Scheduling unrelated parallel machines to minimize total weighted tardiness

Computers and Operations Research
Simulated annealing heuristic for flow shop scheduling problems with unrelated parallel machines

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

A multiobjective optimization approach to solve a parallel machines scheduling problem

Advances in Artificial Intelligence
A particle swarm optimization for a fuzzy multi-objective unrelated parallel machines scheduling problem

Applied Soft Computing

Quantified Score

Hi-index	0.01

Visualization

Abstract

Quality control lead times are one of most significant causes of loss of time in the pharmaceutical and cosmetics industries. This is partly due to the organization of laboratories that feature parallel multipurpose machines for chromatographic analyses. The testing process requires long setup times and operators are needed to launch the process. The various controls are non-preemptive and are characterized by a release date, a due date and available routings. These quality processes lead to significant delays, and we therefore evaluate the total tardiness criterion. Previous heuristics were defined for the total tardiness criterion, parallel machines, and setup such as apparent tardiness cost (ATC) and ATC with setups (ATCS). We propose new rules and a simulated annealing procedure in order to minimize total tardiness.