In this work we consider the hybrid flexible flowline (HFFL) problem with a set of additional constraints that apply in real-world industrial environments. A set of n jobs has to be scheduled on a set of m ordered stages. All jobs are available at time 0, and job preemption is not allowed. Each stage i consists in mi parallel unrelated machines. Jobs might skip stages; we denote the stages visited by job j as the set Fj . At each stage i in Fj , job j should be processed by exactly one machine in the set of eligible machines Eij . Precedence constraints among jobs refrain job j from starting in the first stage before ending the process of its predecessor jobs Pj in the last stage. Setup times Siljk depend on both the previous job j and the next job k, and on the stage i and machine l where the setup is executed. These times can be anticipatory or non-anticipatory. Time lags lagilj between finishing a job j at stage i and starting the job at the next stage, can be positive or negative and depend on the machine l that job j is assigned to at stage i. Machines release dates are given by the input parameter relij. The goal is to find a schedule that minimises the makespan, that is, the maximum job completion time. The gap between HFFL theory and scheduling practice is named in two reviews on HFFL problems [1, 2]. For a more recent review, see [3].
[1]
Heinrich Kuhn,et al.
A taxonomy of flexible flow line scheduling procedures
,
2007,
Eur. J. Oper. Res..
[2]
Richard J. Linn,et al.
Hybrid flow shop scheduling: a survey
,
1999
.
[3]
Rubén Ruiz,et al.
Genetic algorithms with different representation schemes for complex hybrid flexible flow line problems
,
2010,
Int. J. Metaheuristics.
[4]
Michael Pinedo,et al.
Scheduling: Theory, Algorithms, and Systems
,
1994
.
[5]
Rubén Ruiz,et al.
Local Search in Complex Scheduling Problems
,
2007,
SLS.
[6]
Inyong Ham,et al.
A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem
,
1983
.