Metaheuristic algorithms for the multistage hybrid flowshop scheduling problem

The hybrid flow shop scheduling problem

“…[8] presented several heuristics and a SA method for an m-stage HFS that models client-server requests. Another SA method with the same solution representation was given in [88] together with a lower bound to evaluate algorithm performance. This bound was proved wrong and corrected later by [69].…”

“…F Hm, ((P M (k) ) m k=1 ))|avail|several simulation, heuristics, SA [16] F H3, ((P M (k) ) 3 k=1 ))||Cmax agent-based approach [20] F Hm, ((P M (k) ) m k=1 ))|recrc|Ū w MPF, GA, lower bounds,checks processing [47] F Hm, ((P M (k) ) m k=1 ))||Cmax Artificial Immune Systems [91] F Hm, ((P M (k) ) m k=1 ))|blocking, skip|Cmax flow lines, MPF, TS, huristics F H2, ((1 (1) , P 2 (2) ))||Cmax B&B, GA, heuristics [41] F Hm, ((P M (k) ) m k=1 ))|recrc|T w dispatching rules, heuristics [61] F H2, ((1 (1) , P 2 (2) ))|no − wait, (p j = 1) 1 |Cmax exact method [96] F Hm, ((P M (k) ) m k=1 ))||{Cmax,C} review on exact solution methods [121] F H2, ((1 (1) , P M (2) ))|avail|Cmax B&B, heuristics, complexity [38] F H3, ((RM (k) ) 3 k=1 ))|prec, block, S nsd |Cmax MPR-TS [70] F H2, ((P M (k) ) 2 k=1 )||Cmax B&B [88] F Hm, ((P M (k) ) m k=1 ))||Cmax MPR-SA, lower bounds [107] F H2, ((P 2 (1) , 1 (2) ))|batch|Cmax TSP-based heuristics [37] F H3, ((RM (k) ) 3 k=1 ))|S sd , block, prec|Cmax MPF, lower bounds, TS [50] F Hm, ((P M (k) ) m k=1 ))|assign|ĒT TS, special problem [83] F Hm, ((P M (k) ) m k=1 ))|r j |Cost TS, SA, heuristics [85] F Hm, ((RM (k) ) m k=1 ))|lot, skip|Cost GA, SA, flow lines [100] F H3, ((P M (k) ) 3 k=1 ))||Cmax heuristics [151] (1) , P 2 (2) ))|assembly (2) |F heuristics [195] F Hm, ((P M (k) ) m k=1 ))|size jk |Cmax Particle Swarm Optimization [196] F H2, ((1 (1) , P 2 (2) ))|skip (1) |Cmax heuristics 2009 [90] F Hm, ((RM (k) ) m k=1 ))|S sd , r j |αCmax + (1 − α)Ū MPF, heuristics, dispatching rules, GA [95] F H2, ((P M (1) , 1 (2) ))||Cmax heuristics, product-mix [191] F Hm, ((P M (k) ) m k=1 ))|skip, block, reentry|Cmax GA mixed with LS [229] F Hm, ((P M (k) ) m k=1 ))|size jk |Cmax Iterated Greedy (IG) [19] F H2, ((P M (1) , P M (2) ))|batch (2) |Cmax heuris...…”

Algorithms for a realistic variant of flowshop scheduling

“…Notice that the literature on hybrid flowshops, with identical parallel machines per stage and no setups, is plenty. Some recent references are the study of Haouari and Hidri (2008) in lower bounds or the metaheuristics proposed by Jin, Yang and Ito (2006). Flexible flowshops, often referred to as flexible flow line problems, are reviewed in Quadt and Kuhn (2007), among others.…”

Some heuristics for the hybrid flow shop scheduling problem with setup and assembly operations

“…Finally, the sequencing sub-problem is used to sequence the jobs assigned to a machine. Garey and Johnson (1979) showed that the HFS problem with makespan objective is NP-complete, and for years, a large numbers of heuristics and approximation algorithms have been proposed for various HFS configurations (Ying et al, 2006;Ribas et al, 2010;Tseng et al, 2008;Jin et al, 2006). Gupta (1988) showed that HFS is limited to two processing stages, one stage contains at least two machines and the other one includes a single machine and the problem is NP-hard (Khalouli et al, 2010;Yang 2010).…”