Parallel machines scheduling with nonsimultaneous machine available time
Discrete Applied Mathematics
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Computers and Operations Research
Job shop scheduling for missed due-date performance
Computers and Industrial Engineering
Tabu search for total tardiness minimization in flowshop scheduling problems
Computers and Operations Research
Computers and Operations Research
Dynamic rescheduling that simultaneously considers efficiency and stability
Computers and Industrial Engineering
Information Processing Letters
Operations Research
Design and Analysis of Experiments
Design and Analysis of Experiments
Multicriteria Scheduling: Theory, Models and Algorithms
Multicriteria Scheduling: Theory, Models and Algorithms
Computers and Operations Research
A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem
Computers and Operations Research
Computers and Operations Research
Minimizing the bicriteria of makespan and maximum tardiness with an upper bound on maximum tardiness
Computers and Operations Research
Computers and Operations Research
A Review and Evaluation of Multiobjective Algorithms for the Flowshop Scheduling Problem
INFORMS Journal on Computing
A case study on using evolutionary algorithms to optimize bakery production planning
Expert Systems with Applications: An International Journal
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In this paper we study a due date setting problem in a flowshop layout. The problem consists of scheduling a set of jobs arriving to the system together with jobs already present (denoted as old jobs), in order to set a common due date for the new jobs. Since the old jobs have a common due date that must not be violated, our problem is a rescheduling problem with the objective of minimising the makespan of the new jobs (thus obtaining the tightest possible due date for the new jobs) and a constraint since the maximum tardiness of the old jobs must be equal to zero. This approach leads to an interesting scheduling problem in which two different objectives are considered, each one for a subset of the jobs that must be scheduled. To the best of our knowledge, this type of problems have been scarcely considered in the literature, and only for very specific purposes. Since our problem is clearly NP-hard, a new heuristic based on variable neighbourhood search (VNS) has been designed. The computational results show that our proposed heuristic outperforms two existing heuristic methods for similar problems in the literature.