• Aucun résultat trouvé

Job shop scheduling with setup times and maximal time-lags: A simple constraint programming approach

N/A
N/A
Protected

Academic year: 2021

Partager "Job shop scheduling with setup times and maximal time-lags: A simple constraint programming approach"

Copied!
16
0
0

Texte intégral

Loading

Figure

Table 1: SDST-JSP: Comparison vs state-of-the-art (best & mean C max , 10 runs).
Table 2: Results summary for JTL- and NW-JSP.
Table 3: NW-JSP: Comparison vs state-of-the-art on easy instances (best & mean C max , 10 runs).
Table 4: NW-JSP: Improvement on hard instances (best & mean C max , 10 runs).
+3

Références

Documents relatifs

(Dhouib et al., 2012.) studied the permutation flowshop scheduling problem with sequence dependent setup times and time lags constraints of successive operations

To adapt the instances from the literature to the studied problem, the missing data, such as the quantities of dishes, due dates of jobs, machine capacities, and time windows

For each instance, we give the best found lower (LB1) and upper (UB1) bounds, the total number of branch and bound nodes (#nodes), the total CPU time in seconds (CPU), the initial

Motivated by the results in Leary and Michaely (2011) that large and mature U.S. firms and U.S. firms with less volatile cash flows tend to smooth dividends more, we inves- tigate

This chal- lenging real scheduling problem, that emerged in the nowadays printing industry, corresponds to a flexible job shop scheduling problem with sequencing flexibility

Une des particularités de cette loi est qu’elle ouvre la possibilité à un médecin de pratiquer une euthanasie suite à la demande d’un patient, demande pouvant être basée sur une

Without setup times, allowing job splitting makes many scheduling problems trivial: both for minimising make- span and for minimising total (weighted) completion time, an

We have compared the pro- posed approach (denoted as f-NSGA2-LS) against the single-objective genetic algorithm (GA) that works only on the modal value of TFNs (denoted as crisp-GA),